diff --git a/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality Classification Model.ipynb b/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality Classification Model.ipynb new file mode 100644 index 0000000..72f5797 --- /dev/null +++ b/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality Classification Model.ipynb @@ -0,0 +1,1690 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8d4bf69d", + "metadata": {}, + "source": [ + "# Voltage Quality Classification Model\n", + " The quality of power supplied to end-use equipments depends upon the quality of voltage supplied by utility. Voltage is said to have quality if it has rated value at rated frequency without any distortion from sine wave. The normal voltage quality issues are:\n", + "- Voltage Sag\n", + "- Voltage Swell\n", + "- Voltage Flicker\n", + "- Voltage Harmonics\n", + "- Voltage Interruption\n", + "\n", + "Classification of voltage quality is a must for activating corresponding controllers to mitigate the issues using compensating device. Training data is generated by using functions which simulate the above power quality issues." + ] + }, + { + "cell_type": "markdown", + "id": "8ba94acd", + "metadata": {}, + "source": [ + "# Installing the required packages" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "4f7c0ea6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: xgboost in /opt/anaconda3/lib/python3.8/site-packages (1.4.2)\r\n", + "Requirement already satisfied: scipy in /opt/anaconda3/lib/python3.8/site-packages (from xgboost) (1.6.2)\r\n", + "Requirement already satisfied: numpy in /opt/anaconda3/lib/python3.8/site-packages (from xgboost) (1.20.1)\r\n" + ] + } + ], + "source": [ + "!pip install xgboost" + ] + }, + { + "cell_type": "markdown", + "id": "18fc265e", + "metadata": {}, + "source": [ + "# Importing the required libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "c8212aea", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import seaborn as sn\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import rcParams\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.svm import SVC\n", + "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score\n", + "from xgboost import XGBClassifier\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.model_selection import GridSearchCV\n", + "\n", + "%matplotlib inline\n", + "\n", + "import warnings\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "cell_type": "markdown", + "id": "0cf4bd32", + "metadata": {}, + "source": [ + "# Loading the data into the dataframe" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "be3e6804", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Sample Voltage Problem\n", + "0 1 56.46 Normal\n", + "1 2 111.20 Normal\n", + "2 3 162.57 Normal\n", + "3 4 209.00 Normal\n", + "4 5 249.09 Normal" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test.head()" + ] + }, + { + "cell_type": "markdown", + "id": "865fe385", + "metadata": {}, + "source": [ + "# Total number of rows and columns" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "34b1b141", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3366, 3)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.shape # 3366 rows and 3 columns" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "c6fcc035", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(1020, 3)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test.shape" + ] + }, + { + "cell_type": "markdown", + "id": "91147657", + "metadata": {}, + "source": [ + "# Checking the type of data" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a2612df2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 3366 entries, 0 to 3365\n", + "Data columns (total 3 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Sample 3366 non-null int64 \n", + " 1 Voltage 3366 non-null float64\n", + " 2 Problem 3366 non-null object \n", + "dtypes: float64(1), int64(1), object(1)\n", + "memory usage: 79.0+ KB\n" + ] + } + ], + "source": [ + "data.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "4bda0fc9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1020 entries, 0 to 1019\n", + "Data columns (total 3 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Sample 1020 non-null int64 \n", + " 1 Voltage 1020 non-null float64\n", + " 2 Problem 1020 non-null object \n", + "dtypes: float64(1), int64(1), object(1)\n", + "memory usage: 24.0+ KB\n" + ] + } + ], + "source": [ + "test.info()" + ] + }, + { + "cell_type": "markdown", + "id": "593b3e7c", + "metadata": {}, + "source": [ + "# Checking for missing values" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a62ca453", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sample 0\n", + "Voltage 0\n", + "Problem 0\n", + "dtype: int64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.isnull().sum() # No missing values" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "ddf6406b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Sample 0\n", + "Voltage 0\n", + "Problem 0\n", + "dtype: int64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "id": "451f6cda", + "metadata": {}, + "source": [ + "# Checking for duplicates" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "48f717bc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "510" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.duplicated().sum() # 510 duplicates" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "f1aa7d57", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "136" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test.duplicated().sum()" + ] + }, + { + "cell_type": "markdown", + "id": "2f7bc812", + "metadata": {}, + "source": [ + "# Finding the unique values in problem column" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "66c66225", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Normal', 'Sag', 'Swell', 'Flicker', 'Interruption', 'Harmonics'],\n", + " dtype=object)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.Problem.unique() # 6 unique values" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "e0974cd2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Normal', 'Sag', 'Swell', 'Flicker', 'Interruption', 'Harmonics'],\n", + " dtype=object)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test.Problem.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "99109e7f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Sample Voltage Problem\n", + "0 1 56.46 Normal\n", + "1 2 111.20 Normal\n", + "2 3 162.57 Normal\n", + "3 4 209.00 Normal\n", + "4 5 249.09 Normal" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.head()" + ] + }, + { + "cell_type": "markdown", + "id": "1410da43", + "metadata": {}, + "source": [ + "# Analysing statistical data" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "d35d8713", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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SampleVoltageProblem
count3366.0000003366.0000003366
uniqueNaNNaN6
topNaNNaNHarmonics
freqNaNNaN578
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" + ], + "text/plain": [ + " Sample Voltage Problem\n", + "count 3366.000000 3366.000000 3366\n", + "unique NaN NaN 6\n", + "top NaN NaN Harmonics\n", + "freq NaN NaN 578\n", + "mean 17.500000 0.000226 NaN\n", + "std 9.812166 229.620084 NaN\n", + "min 1.000000 -585.480000 NaN\n", + "25% 9.000000 -208.957500 NaN\n", + "50% 17.500000 0.000000 NaN\n", + "75% 26.000000 209.255000 NaN\n", + "max 34.000000 585.480000 NaN" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.describe(include=\"all\")" + ] + }, + { + "cell_type": "markdown", + "id": "553a108e", + "metadata": {}, + "source": [ + "# Finding outliers" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "51229178", + "metadata": {}, + "outputs": [], + "source": [ + "# Function to find the outliers\n", + "def findoutliers(column):\n", + " outliers=[]\n", + " Q1=column.quantile(.25)\n", + " Q3=column.quantile(.75)\n", + " IQR=Q3-Q1\n", + " lower_limit=Q1-(1.5*IQR)\n", + " upper_limit=Q3+(1.5*IQR)\n", + " for out1 in column:\n", + " if out1>upper_limit or out1 " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Voltage\n", + "fix, (ax1,ax2) =plt.subplots(1,2,figsize=(7,5))\n", + "sn.boxplot(data.Voltage, orient='v',ax=ax1)\n", + "ax1.set_ylabel=data.Voltage.name\n", + "ax1.set_title('Box plot of {}'.format(data.Voltage.name))\n", + "sn.distplot(data.Voltage,ax=ax2) \n", + "ax2.set_title('Distribution plot of {}'.format(data.Voltage.name))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "784eada8", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Harmonics 578\n", + "Swell 578\n", + "Sag 578\n", + "Normal 578\n", + "Flicker 544\n", + "Interruption 510\n", + "Name: Problem, dtype: int64" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Problem\n", + "data.Problem.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "012d7672", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pl = sn.factorplot('Problem',data=data, aspect=4,kind='count')\n", + "pl.set_xticklabels()" + ] + }, + { + "cell_type": "markdown", + "id": "07cb4c79", + "metadata": {}, + "source": [ + "# Identifying the independent and dependent variables" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "d18b49b6", + "metadata": {}, + "outputs": [], + "source": [ + "X = data.iloc[:,:-1] # Independent variable\n", + "y = data.Problem # Dependent variable" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "a22d8277", + "metadata": {}, + "outputs": [], + "source": [ + "x_test = test.iloc[:,:-1]\n", + "y_test = test.Problem " + ] + }, + { + "cell_type": "markdown", + "id": "57dfd617", + "metadata": {}, + "source": [ + "# Decision Tree" + ] + }, + { + "cell_type": "markdown", + "id": "50e0afdc", + "metadata": {}, + "source": [ + "# Defining the model" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "56e08b15", + "metadata": {}, + "outputs": [], + "source": [ + "model_dt = DecisionTreeClassifier()" + ] + }, + { + "cell_type": "markdown", + "id": "0626248b", + "metadata": {}, + "source": [ + "# Training the model" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "91e5d0f2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DecisionTreeClassifier()" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_dt.fit(X,y)" + ] + }, + { + "cell_type": "markdown", + "id": "7a358b81", + "metadata": {}, + "source": [ + "# Testing the model" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "5ef648e8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.95" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_predict_dt = model_dt.predict(x_test)\n", + "as_dt = accuracy_score(y_test,y_predict_dt)\n", + "as_dt" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "894932ae", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " Flicker 0.92 1.00 0.96 170\n", + " Harmonics 0.91 0.85 0.88 170\n", + "Interruption 1.00 1.00 1.00 170\n", + " Normal 0.95 1.00 0.97 170\n", + " Sag 0.98 0.92 0.95 170\n", + " Swell 0.95 0.92 0.93 170\n", + "\n", + " accuracy 0.95 1020\n", + " macro avg 0.95 0.95 0.95 1020\n", + "weighted avg 0.95 0.95 0.95 1020\n", + "\n" + ] + } + ], + "source": [ + "print(classification_report(y_test,y_predict_dt))" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "d9a53648", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[170, 0, 0, 0, 0, 0],\n", + " [ 7, 145, 0, 5, 4, 9],\n", + " [ 0, 0, 170, 0, 0, 0],\n", + " [ 0, 0, 0, 170, 0, 0],\n", + " [ 3, 10, 0, 0, 157, 0],\n", + " [ 4, 5, 0, 4, 0, 157]])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "confusion_matrix(y_test,y_predict_dt)" + ] + }, + { + "cell_type": "markdown", + "id": "03be07e5", + "metadata": {}, + "source": [ + "# XGBoost" + ] + }, + { + "cell_type": "markdown", + "id": "10b72622", + "metadata": {}, + "source": [ + "# Defining the model" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "d9b1d0d6", + "metadata": {}, + "outputs": [], + "source": [ + "model_xgb = XGBClassifier(n_estimators=300)" + ] + }, + { + "cell_type": "markdown", + "id": "473fe685", + "metadata": {}, + "source": [ + "# Training the model" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "10d8cbdc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[21:26:24] WARNING: /opt/concourse/worker/volumes/live/7a2b9f41-3287-451b-6691-43e9a6c0910f/volume/xgboost-split_1619728204606/work/src/learner.cc:1061: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'multi:softprob' was changed from 'merror' to 'mlogloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n" + ] + }, + { + "data": { + "text/plain": [ + "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n", + " colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1,\n", + " importance_type='gain', interaction_constraints='',\n", + " learning_rate=0.300000012, max_delta_step=0, max_depth=6,\n", + " min_child_weight=1, missing=nan, monotone_constraints='()',\n", + " n_estimators=300, n_jobs=16, num_parallel_tree=1,\n", + " objective='multi:softprob', random_state=0, reg_alpha=0,\n", + " reg_lambda=1, scale_pos_weight=None, subsample=1,\n", + " tree_method='exact', validate_parameters=1, verbosity=None)" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_xgb.fit(X,y)" + ] + }, + { + "cell_type": "markdown", + "id": "8ffd720a", + "metadata": {}, + "source": [ + "# Testing the model" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "ab0a0c92", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.95" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_predict_xgb = model_dt.predict(x_test)\n", + "as_xgb = accuracy_score(y_test,y_predict_xgb)\n", + "as_xgb" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "f98f8111", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " Flicker 0.92 1.00 0.96 170\n", + " Harmonics 0.91 0.85 0.88 170\n", + "Interruption 1.00 1.00 1.00 170\n", + " Normal 0.95 1.00 0.97 170\n", + " Sag 0.98 0.92 0.95 170\n", + " Swell 0.95 0.92 0.93 170\n", + "\n", + " accuracy 0.95 1020\n", + " macro avg 0.95 0.95 0.95 1020\n", + "weighted avg 0.95 0.95 0.95 1020\n", + "\n" + ] + } + ], + "source": [ + "print(classification_report(y_test,y_predict_xgb))" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "ebdecc0c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[170, 0, 0, 0, 0, 0],\n", + " [ 7, 145, 0, 5, 4, 9],\n", + " [ 0, 0, 170, 0, 0, 0],\n", + " [ 0, 0, 0, 170, 0, 0],\n", + " [ 3, 10, 0, 0, 157, 0],\n", + " [ 4, 5, 0, 4, 0, 157]])" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "confusion_matrix(y_test,y_predict_xgb)" + ] + }, + { + "cell_type": "markdown", + "id": "f5dc8e32", + "metadata": {}, + "source": [ + "# Random Forest" + ] + }, + { + "cell_type": "markdown", + "id": "d8d6a4f0", + "metadata": {}, + "source": [ + "# Defining the model" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "8a51ef49", + "metadata": {}, + "outputs": [], + "source": [ + "model_rf = RandomForestClassifier()" + ] + }, + { + "cell_type": "markdown", + "id": "11bf5e15", + "metadata": {}, + "source": [ + "# Training the model" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "8c568b29", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "RandomForestClassifier()" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_rf.fit(X,y)" + ] + }, + { + "cell_type": "markdown", + "id": "bb844013", + "metadata": {}, + "source": [ + "# Testing the model" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "654580cb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9774509803921568" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_predict_rf = model_rf.predict(x_test)\n", + "as_rf = accuracy_score(y_test,y_predict_rf)\n", + "as_rf" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "afa6cdb1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " Flicker 0.97 1.00 0.99 170\n", + " Harmonics 0.94 0.92 0.93 170\n", + "Interruption 1.00 1.00 1.00 170\n", + " Normal 1.00 1.00 1.00 170\n", + " Sag 0.98 0.96 0.97 170\n", + " Swell 0.97 0.98 0.97 170\n", + "\n", + " accuracy 0.98 1020\n", + " macro avg 0.98 0.98 0.98 1020\n", + "weighted avg 0.98 0.98 0.98 1020\n", + "\n" + ] + } + ], + "source": [ + "print(classification_report(y_test,y_predict_rf))" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "cba6c72b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[170, 0, 0, 0, 0, 0],\n", + " [ 5, 157, 0, 0, 3, 5],\n", + " [ 0, 0, 170, 0, 0, 0],\n", + " [ 0, 0, 0, 170, 0, 0],\n", + " [ 0, 6, 0, 0, 164, 0],\n", + " [ 0, 4, 0, 0, 0, 166]])" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "confusion_matrix(y_test,y_predict_rf)" + ] + }, + { + "cell_type": "markdown", + "id": "80d38c0b", + "metadata": {}, + "source": [ + "# Model Evaluation" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "aa4afe29", + "metadata": {}, + "outputs": [], + "source": [ + "Accuracy_Score = [as_dt,as_rf,as_xgb]\n", + "Models = ['Decision Tree', 'Random Forest','XG Boost']" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "bae685ee", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sn.barplot(Accuracy_Score, Models, color=\"r\")\n", + "plt.xlabel('Accuracy Score')\n", + "plt.title('Accuracy Score')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "e59d07ca", + "metadata": {}, + "source": [ + "Random Forest seems to have the highest accuracy score hence we go ahead with Random Forest algorithm." + ] + }, + { + "cell_type": "markdown", + "id": "f20c8195", + "metadata": {}, + "source": [ + "# Hyperparameter (using grid search)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "e513bf46", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 5 folds for each of 120 candidates, totalling 600 fits\n" + ] + }, + { + "data": { + "text/plain": [ + "GridSearchCV(cv=5, estimator=RandomForestClassifier(),\n", + " param_grid={'max_depth': [10, 15, 14, 13, 12],\n", + " 'n_estimators': [150, 160, 170, 180, 190, 200],\n", + " 'random_state': [4, 5, 6, 7]},\n", + " verbose=1)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "parameters = {'max_depth':[10,15,14,13,12],\n", + " 'random_state': [4,5,6,7],\n", + " 'n_estimators':[150,160,170,180,190,200]}\n", + "\n", + "grid = GridSearchCV(model_rf,parameters,cv=5,verbose=1)\n", + "grid.fit(X,y)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "10a4aca4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.8773607700142415" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grid.best_score_" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "94bb569e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'max_depth': 13, 'n_estimators': 190, 'random_state': 5}" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "grid.best_params_" + ] + }, + { + "cell_type": "markdown", + "id": "71b111fc", + "metadata": {}, + "source": [ + "# Training Random Forest with best parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "0ee81152", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "RandomForestClassifier(max_depth=13, n_estimators=190, random_state=5)" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_rf = RandomForestClassifier(n_estimators=190,max_depth=13,random_state=5)\n", + "model_rf.fit(X,y)" + ] + }, + { + "cell_type": "markdown", + "id": "77dd9b12", + "metadata": {}, + "source": [ + "# Testing Random Forest with best parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "ed03903a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9892156862745098" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_predict = model_rf.predict(x_test)\n", + "accuracy_score(y_test,y_predict)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "96b24b5a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " Flicker 1.00 1.00 1.00 170\n", + " Harmonics 0.94 1.00 0.97 170\n", + "Interruption 1.00 1.00 1.00 170\n", + " Normal 1.00 1.00 1.00 170\n", + " Sag 1.00 0.96 0.98 170\n", + " Swell 1.00 0.98 0.99 170\n", + "\n", + " accuracy 0.99 1020\n", + " macro avg 0.99 0.99 0.99 1020\n", + "weighted avg 0.99 0.99 0.99 1020\n", + "\n" + ] + } + ], + "source": [ + "print(classification_report(y_test,y_predict))" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "9b77ef9f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[170, 0, 0, 0, 0, 0],\n", + " [ 0, 170, 0, 0, 0, 0],\n", + " [ 0, 0, 170, 0, 0, 0],\n", + " [ 0, 0, 0, 170, 0, 0],\n", + " [ 0, 7, 0, 0, 163, 0],\n", + " [ 0, 4, 0, 0, 0, 166]])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "confusion_matrix(y_test,y_predict)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "596a373a", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality Test.csv b/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality Test.csv new file mode 100644 index 0000000..77a5450 --- /dev/null +++ b/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality Test.csv @@ -0,0 +1 @@ +Sample,Voltage,Problem 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,43.47,Sag 2,85.63,Sag 3,125.18,Sag 4,160.93,Sag 5,191.8,Sag 6,216.85,Sag 7,235.31,Sag 8,246.63,Sag 9,250.46,Sag 10,246.68,Sag 11,235.42,Sag 12,217.01,Sag 13,192.02,Sag 14,161.19,Sag 15,125.47,Sag 16,85.94,Sag 17,43.8,Sag 18,-43.14,Sag 19,-85.31,Sag 20,-124.89,Sag 21,-160.68,Sag 22,-191.59,Sag 23,-216.68,Sag 24,-235.19,Sag 25,-246.57,Sag 26,-250.46,Sag 27,-246.74,Sag 28,-235.54,Sag 29,-217.18,Sag 30,-192.23,Sag 31,-161.45,Sag 32,-125.76,Sag 33,-86.26,Sag 34,-44.13,Sag 1,37.83,Sag 2,74.51,Sag 3,108.92,Sag 4,140.03,Sag 5,166.89,Sag 6,188.68,Sag 7,204.75,Sag 8,214.6,Sag 9,217.93,Sag 10,214.65,Sag 11,204.85,Sag 12,188.83,Sag 13,167.08,Sag 14,140.26,Sag 15,109.18,Sag 16,74.78,Sag 17,38.12,Sag 18,-37.54,Sag 19,-74.23,Sag 20,-108.67,Sag 21,-139.81,Sag 22,-166.7,Sag 23,-188.54,Sag 24,-204.65,Sag 25,-214.55,Sag 26,-217.93,Sag 27,-214.7,Sag 28,-204.95,Sag 29,-188.98,Sag 30,-167.27,Sag 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32,-173.13,Flicker 33,-118.74,Flicker 34,-60.76,Flicker 1,54.2,Flicker 2,106.75,Flicker 3,156.07,Flicker 4,200.64,Flicker 5,239.13,Flicker 6,270.35,Flicker 7,293.37,Flicker 8,307.48,Flicker 9,312.26,Flicker 10,307.55,Flicker 11,293.51,Flicker 12,270.56,Flicker 13,239.4,Flicker 14,200.97,Flicker 15,156.43,Flicker 16,107.15,Flicker 17,54.61,Flicker 18,-53.79,Flicker 19,-106.36,Flicker 20,-155.71,Flicker 21,-200.32,Flicker 22,-238.86,Flicker 23,-270.14,Flicker 24,-293.23,Flicker 25,-307.41,Flicker 26,-312.26,Flicker 27,-307.63,Flicker 28,-293.66,Flicker 29,-270.77,Flicker 30,-239.67,Flicker 31,-201.29,Flicker 32,-156.79,Flicker 33,-107.54,Flicker 34,-55.03,Flicker 1,54.76,Flicker 2,107.87,Flicker 3,157.69,Flicker 4,202.73,Flicker 5,241.62,Flicker 6,273.17,Flicker 7,296.43,Flicker 8,310.68,Flicker 9,315.51,Flicker 10,310.76,Flicker 11,296.57,Flicker 12,273.38,Flicker 13,241.89,Flicker 14,203.06,Flicker 15,158.06,Flicker 16,108.26,Flicker 17,55.18,Flicker 18,-54.35,Flicker 19,-107.47,Flicker 20,-157.33,Flicker 21,-202.41,Flicker 22,-241.35,Flicker 23,-272.96,Flicker 24,-296.28,Flicker 25,-310.61,Flicker 26,-315.51,Flicker 27,-310.83,Flicker 28,-296.72,Flicker 29,-273.59,Flicker 30,-242.16,Flicker 31,-203.38,Flicker 32,-158.43,Flicker 33,-108.66,Flicker 34,-55.6,Flicker 1,3.95,Interruption 2,7.78,Interruption 3,11.38,Interruption 4,14.63,Interruption 5,17.44,Interruption 6,19.71,Interruption 7,21.39,Interruption 8,22.42,Interruption 9,22.77,Interruption 10,22.43,Interruption 11,21.4,Interruption 12,19.73,Interruption 13,17.46,Interruption 14,14.65,Interruption 15,11.41,Interruption 16,7.81,Interruption 17,3.98,Interruption 18,-3.92,Interruption 19,-7.76,Interruption 20,-11.35,Interruption 21,-14.61,Interruption 22,-17.42,Interruption 23,-19.7,Interruption 24,-21.38,Interruption 25,-22.42,Interruption 26,-22.77,Interruption 27,-22.43,Interruption 28,-21.41,Interruption 29,-19.74,Interruption 30,-17.48,Interruption 31,-14.68,Interruption 32,-11.43,Interruption 33,-7.84,Interruption 34,-4.01,Interruption 1,3.39,Interruption 2,6.67,Interruption 3,9.75,Interruption 4,12.54,Interruption 5,14.95,Interruption 6,16.9,Interruption 7,18.34,Interruption 8,19.22,Interruption 9,19.52,Interruption 10,19.22,Interruption 11,18.34,Interruption 12,16.91,Interruption 13,14.96,Interruption 14,12.56,Interruption 15,9.78,Interruption 16,6.7,Interruption 17,3.41,Interruption 18,-3.36,Interruption 19,-6.65,Interruption 20,-9.73,Interruption 21,-12.52,Interruption 22,-14.93,Interruption 23,-16.88,Interruption 24,-18.33,Interruption 25,-19.21,Interruption 26,-19.52,Interruption 27,-19.23,Interruption 28,-18.35,Interruption 29,-16.92,Interruption 30,-14.98,Interruption 31,-12.58,Interruption 32,-9.8,Interruption 33,-6.72,Interruption 34,-3.44,Interruption 1,2.82,Interruption 2,5.56,Interruption 3,8.13,Interruption 4,10.45,Interruption 5,12.45,Interruption 6,14.08,Interruption 7,15.28,Interruption 8,16.01,Interruption 9,16.26,Interruption 10,16.02,Interruption 11,15.29,Interruption 12,14.09,Interruption 13,12.47,Interruption 14,10.47,Interruption 15,8.15,Interruption 16,5.58,Interruption 17,2.84,Interruption 18,-2.8,Interruption 19,-5.54,Interruption 20,-8.11,Interruption 21,-10.43,Interruption 22,-12.44,Interruption 23,-14.07,Interruption 24,-15.27,Interruption 25,-16.01,Interruption 26,-16.26,Interruption 27,-16.02,Interruption 28,-15.29,Interruption 29,-14.1,Interruption 30,-12.48,Interruption 31,-10.48,Interruption 32,-8.17,Interruption 33,-5.6,Interruption 34,-2.87,Interruption 1,2.26,Interruption 2,4.45,Interruption 3,6.5,Interruption 4,8.36,Interruption 5,9.96,Interruption 6,11.26,Interruption 7,12.22,Interruption 8,12.81,Interruption 9,13.01,Interruption 10,12.81,Interruption 11,12.23,Interruption 12,11.27,Interruption 13,9.97,Interruption 14,8.37,Interruption 15,6.52,Interruption 16,4.46,Interruption 17,2.28,Interruption 18,-2.24,Interruption 19,-4.43,Interruption 20,-6.49,Interruption 21,-8.35,Interruption 22,-9.95,Interruption 23,-11.26,Interruption 24,-12.22,Interruption 25,-12.81,Interruption 26,-13.01,Interruption 27,-12.82,Interruption 28,-12.24,Interruption 29,-11.28,Interruption 30,-9.99,Interruption 31,-8.39,Interruption 32,-6.53,Interruption 33,-4.48,Interruption 34,-2.29,Interruption 1,1.13,Interruption 2,2.22,Interruption 3,3.25,Interruption 4,4.18,Interruption 5,4.98,Interruption 6,5.63,Interruption 7,6.11,Interruption 8,6.41,Interruption 9,6.51,Interruption 10,6.41,Interruption 11,6.11,Interruption 12,5.64,Interruption 13,4.99,Interruption 14,4.19,Interruption 15,3.26,Interruption 16,2.23,Interruption 17,1.14,Interruption 18,-1.12,Interruption 19,-2.22,Interruption 20,-3.24,Interruption 21,-4.17,Interruption 22,-4.98,Interruption 23,-5.63,Interruption 24,-6.11,Interruption 25,-6.4,Interruption 26,-6.51,Interruption 27,-6.41,Interruption 28,-6.12,Interruption 29,-5.64,Interruption 30,-4.99,Interruption 31,-4.19,Interruption 32,-3.27,Interruption 33,-2.24,Interruption 34,-1.15,Interruption 1,204.75,Harmonics 2,299.85,Harmonics 3,280.91,Harmonics 4,235.1,Harmonics 5,234.03,Harmonics 6,265.42,Harmonics 7,275.65,Harmonics 8,252.21,Harmonics 9,235.12,Harmonics 10,251.99,Harmonics 11,275.57,Harmonics 12,265.64,Harmonics 13,234.21,Harmonics 14,234.88,Harmonics 15,280.53,Harmonics 16,300.07,Harmonics 17,205.99,Harmonics 18,-203.51,Harmonics 19,-299.63,Harmonics 20,-281.29,Harmonics 21,-235.32,Harmonics 22,-233.85,Harmonics 23,-265.2,Harmonics 24,-275.72,Harmonics 25,-252.43,Harmonics 26,-235.12,Harmonics 27,-251.77,Harmonics 28,-275.48,Harmonics 29,-265.85,Harmonics 30,-234.4,Harmonics 31,-234.66,Harmonics 32,-280.14,Harmonics 33,-300.28,Harmonics 34,-207.22,Harmonics 1,206.38,Harmonics 2,301.92,Harmonics 3,282.2,Harmonics 4,235.38,Harmonics 5,233.86,Harmonics 6,265.24,Harmonics 7,275.32,Harmonics 8,251.46,Harmonics 9,234.13,Harmonics 10,251.24,Harmonics 11,275.24,Harmonics 12,265.46,Harmonics 13,234.04,Harmonics 14,235.16,Harmonics 15,281.81,Harmonics 16,302.13,Harmonics 17,207.62,Harmonics 18,-205.12,Harmonics 19,-301.7,Harmonics 20,-282.59,Harmonics 21,-235.61,Harmonics 22,-233.68,Harmonics 23,-265.02,Harmonics 24,-275.4,Harmonics 25,-251.68,Harmonics 26,-234.13,Harmonics 27,-251.02,Harmonics 28,-275.15,Harmonics 29,-265.68,Harmonics 30,-234.23,Harmonics 31,-234.94,Harmonics 32,-281.42,Harmonics 33,-302.34,Harmonics 34,-208.86,Harmonics 1,207.85,Harmonics 2,303.8,Harmonics 3,283.38,Harmonics 4,235.64,Harmonics 5,233.71,Harmonics 6,265.08,Harmonics 7,275.02,Harmonics 8,250.78,Harmonics 9,233.23,Harmonics 10,250.56,Harmonics 11,274.93,Harmonics 12,265.3,Harmonics 13,233.89,Harmonics 14,235.41,Harmonics 15,282.98,Harmonics 16,304.01,Harmonics 17,209.11,Harmonics 18,-206.59,Harmonics 19,-303.58,Harmonics 20,-283.78,Harmonics 21,-235.88,Harmonics 22,-233.53,Harmonics 23,-264.86,Harmonics 24,-275.1,Harmonics 25,-251.01,Harmonics 26,-233.23,Harmonics 27,-250.33,Harmonics 28,-274.85,Harmonics 29,-265.52,Harmonics 30,-234.08,Harmonics 31,-235.19,Harmonics 32,-282.59,Harmonics 33,-304.21,Harmonics 34,-210.36,Harmonics 1,209.33,Harmonics 2,305.68,Harmonics 3,284.56,Harmonics 4,235.9,Harmonics 5,233.56,Harmonics 6,264.92,Harmonics 7,274.72,Harmonics 8,250.11,Harmonics 9,232.33,Harmonics 10,249.88,Harmonics 11,274.63,Harmonics 12,265.14,Harmonics 13,233.74,Harmonics 14,235.67,Harmonics 15,284.16,Harmonics 16,305.89,Harmonics 17,210.59,Harmonics 18,-208.06,Harmonics 19,-305.46,Harmonics 20,-284.96,Harmonics 21,-236.14,Harmonics 22,-233.38,Harmonics 23,-264.7,Harmonics 24,-274.81,Harmonics 25,-250.33,Harmonics 26,-232.34,Harmonics 27,-249.65,Harmonics 28,-274.54,Harmonics 29,-265.35,Harmonics 30,-233.93,Harmonics 31,-235.43,Harmonics 32,-283.75,Harmonics 33,-306.09,Harmonics 34,-211.85,Harmonics 1,210.81,Harmonics 2,307.56,Harmonics 3,285.74,Harmonics 4,236.16,Harmonics 5,233.41,Harmonics 6,264.76,Harmonics 7,274.42,Harmonics 8,249.43,Harmonics 9,231.44,Harmonics 10,249.2,Harmonics 11,274.33,Harmonics 12,264.98,Harmonics 13,233.59,Harmonics 14,235.92,Harmonics 15,285.33,Harmonics 16,307.76,Harmonics 17,212.08,Harmonics 18,-209.53,Harmonics 19,-307.34,Harmonics 20,-286.15,Harmonics 21,-236.41,Harmonics 22,-233.24,Harmonics 23,-264.54,Harmonics 24,-274.51,Harmonics 25,-249.66,Harmonics 26,-231.44,Harmonics 27,-248.97,Harmonics 28,-274.24,Harmonics 29,-265.19,Harmonics 30,-233.77,Harmonics 31,-235.68,Harmonics 32,-284.91,Harmonics 33,-307.96,Harmonics 34,-213.34,Harmonics diff --git a/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality.csv b/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality.csv new file mode 100644 index 0000000..2b55a95 --- /dev/null +++ b/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality.csv @@ -0,0 +1 @@ +Sample,Voltage,Problem 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.55,Normal 2,111.38,Normal 3,162.84,Normal 4,209.35,Normal 5,249.5,Normal 6,282.08,Normal 7,306.09,Normal 8,320.82,Normal 9,325.8,Normal 10,320.89,Normal 11,306.24,Normal 12,282.3,Normal 13,249.78,Normal 14,209.68,Normal 15,163.22,Normal 16,111.8,Normal 17,56.98,Normal 18,-56.12,Normal 19,-110.97,Normal 20,-162.46,Normal 21,-209.01,Normal 22,-249.22,Normal 23,-281.86,Normal 24,-305.94,Normal 25,-320.74,Normal 26,-325.8,Normal 27,-320.97,Normal 28,-306.39,Normal 29,-282.51,Normal 30,-250.06,Normal 31,-210.01,Normal 32,-163.59,Normal 33,-112.21,Normal 34,-57.41,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 31,-209.67,Normal 32,-163.33,Normal 33,-112.02,Normal 34,-57.32,Normal 1,56.46,Normal 2,111.2,Normal 3,162.57,Normal 4,209,Normal 5,249.09,Normal 6,281.62,Normal 7,305.59,Normal 8,320.29,Normal 9,325.27,Normal 10,320.37,Normal 11,305.74,Normal 12,281.84,Normal 13,249.37,Normal 14,209.34,Normal 15,162.95,Normal 16,111.61,Normal 17,56.89,Normal 18,-56.03,Normal 19,-110.79,Normal 20,-162.19,Normal 21,-208.67,Normal 22,-248.81,Normal 23,-281.4,Normal 24,-305.45,Normal 25,-320.22,Normal 26,-325.27,Normal 27,-320.44,Normal 28,-305.89,Normal 29,-282.05,Normal 30,-249.65,Normal 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15,15.48,Interruption 16,10.6,Interruption 17,5.4,Interruption 18,-5.32,Interruption 19,-10.53,Interruption 20,-15.41,Interruption 21,-19.82,Interruption 22,-23.64,Interruption 23,-26.73,Interruption 24,-29.02,Interruption 25,-30.42,Interruption 26,-30.9,Interruption 27,-30.44,Interruption 28,-29.06,Interruption 29,-26.79,Interruption 30,-23.72,Interruption 31,-19.92,Interruption 32,-15.52,Interruption 33,-10.64,Interruption 34,-5.45,Interruption 1,5.08,Interruption 2,10.01,Interruption 3,14.63,Interruption 4,18.81,Interruption 5,22.42,Interruption 6,25.34,Interruption 7,27.5,Interruption 8,28.82,Interruption 9,29.27,Interruption 10,28.83,Interruption 11,27.51,Interruption 12,25.36,Interruption 13,22.44,Interruption 14,18.84,Interruption 15,14.66,Interruption 16,10.04,Interruption 17,5.12,Interruption 18,-5.04,Interruption 19,-9.97,Interruption 20,-14.6,Interruption 21,-18.78,Interruption 22,-22.39,Interruption 23,-25.32,Interruption 24,-27.49,Interruption 25,-28.82,Interruption 26,-29.27,Interruption 27,-28.84,Interruption 28,-27.53,Interruption 29,-25.38,Interruption 30,-22.47,Interruption 31,-18.87,Interruption 32,-14.7,Interruption 33,-10.08,Interruption 34,-5.16,Interruption 1,4.8,Interruption 2,9.45,Interruption 3,13.82,Interruption 4,17.77,Interruption 5,21.17,Interruption 6,23.94,Interruption 7,25.98,Interruption 8,27.23,Interruption 9,27.65,Interruption 10,27.23,Interruption 11,25.99,Interruption 12,23.96,Interruption 13,21.2,Interruption 14,17.8,Interruption 15,13.85,Interruption 16,9.49,Interruption 17,4.84,Interruption 18,-4.76,Interruption 19,-9.42,Interruption 20,-13.79,Interruption 21,-17.74,Interruption 22,-21.15,Interruption 23,-23.92,Interruption 24,-25.96,Interruption 25,-27.22,Interruption 26,-27.65,Interruption 27,-27.24,Interruption 28,-26,Interruption 29,-23.98,Interruption 30,-21.22,Interruption 31,-17.82,Interruption 32,-13.88,Interruption 33,-9.52,Interruption 34,-4.87,Interruption 1,4.52,Interruption 2,8.9,Interruption 3,13,Interruption 4,16.72,Interruption 5,19.93,Interruption 6,22.53,Interruption 7,24.45,Interruption 8,25.62,Interruption 9,26.02,Interruption 10,25.63,Interruption 11,24.46,Interruption 12,22.55,Interruption 13,19.95,Interruption 14,16.75,Interruption 15,13.04,Interruption 16,8.93,Interruption 17,4.55,Interruption 18,-4.48,Interruption 19,-8.86,Interruption 20,-12.97,Interruption 21,-16.69,Interruption 22,-19.9,Interruption 23,-22.51,Interruption 24,-24.43,Interruption 25,-25.62,Interruption 26,-26.02,Interruption 27,-25.63,Interruption 28,-24.47,Interruption 29,-22.56,Interruption 30,-19.97,Interruption 31,-16.77,Interruption 32,-13.07,Interruption 33,-8.96,Interruption 34,-4.59,Interruption 1,3.95,Interruption 2,7.78,Interruption 3,11.37,Interruption 4,14.62,Interruption 5,17.42,Interruption 6,19.7,Interruption 7,21.37,Interruption 8,22.4,Interruption 9,22.75,Interruption 10,22.41,Interruption 11,21.38,Interruption 12,19.71,Interruption 13,17.44,Interruption 14,14.64,Interruption 15,11.4,Interruption 16,7.81,Interruption 17,3.98,Interruption 18,-3.92,Interruption 19,-7.75,Interruption 20,-11.34,Interruption 21,-14.59,Interruption 22,-17.4,Interruption 23,-19.68,Interruption 24,-21.36,Interruption 25,-22.4,Interruption 26,-22.75,Interruption 27,-22.41,Interruption 28,-21.39,Interruption 29,-19.73,Interruption 30,-17.46,Interruption 31,-14.66,Interruption 32,-11.42,Interruption 33,-7.84,Interruption 34,-4.01,Interruption 1,3.39,Interruption 2,6.67,Interruption 3,9.76,Interruption 4,12.54,Interruption 5,14.95,Interruption 6,16.9,Interruption 7,18.34,Interruption 8,19.22,Interruption 9,19.52,Interruption 10,19.23,Interruption 11,18.35,Interruption 12,16.91,Interruption 13,14.97,Interruption 14,12.56,Interruption 15,9.78,Interruption 16,6.7,Interruption 17,3.41,Interruption 18,-3.36,Interruption 19,-6.65,Interruption 20,-9.73,Interruption 21,-12.52,Interruption 22,-14.93,Interruption 23,-16.89,Interruption 24,-18.33,Interruption 25,-19.22,Interruption 26,-19.52,Interruption 27,-19.23,Interruption 28,-18.36,Interruption 29,-16.93,Interruption 30,-14.98,Interruption 31,-12.58,Interruption 32,-9.8,Interruption 33,-6.72,Interruption 34,-3.44,Interruption 1,2.82,Interruption 2,5.56,Interruption 3,8.12,Interruption 4,10.44,Interruption 5,12.44,Interruption 6,14.07,Interruption 7,15.27,Interruption 8,16,Interruption 9,16.25,Interruption 10,16.01,Interruption 11,15.27,Interruption 12,14.08,Interruption 13,12.46,Interruption 14,10.46,Interruption 15,8.14,Interruption 16,5.58,Interruption 17,2.84,Interruption 18,-2.8,Interruption 19,-5.54,Interruption 20,-8.1,Interruption 21,-10.42,Interruption 22,-12.43,Interruption 23,-14.06,Interruption 24,-15.26,Interruption 25,-16,Interruption 26,-16.25,Interruption 27,-16.01,Interruption 28,-15.28,Interruption 29,-14.09,Interruption 30,-12.47,Interruption 31,-10.47,Interruption 32,-8.16,Interruption 33,-5.6,Interruption 34,-2.86,Interruption 1,2.26,Interruption 2,4.45,Interruption 3,6.5,Interruption 4,8.36,Interruption 5,9.96,Interruption 6,11.26,Interruption 7,12.22,Interruption 8,12.81,Interruption 9,13.01,Interruption 10,12.81,Interruption 11,12.23,Interruption 12,11.27,Interruption 13,9.97,Interruption 14,8.37,Interruption 15,6.52,Interruption 16,4.46,Interruption 17,2.28,Interruption 18,-2.24,Interruption 19,-4.43,Interruption 20,-6.49,Interruption 21,-8.35,Interruption 22,-9.95,Interruption 23,-11.26,Interruption 24,-12.22,Interruption 25,-12.81,Interruption 26,-13.01,Interruption 27,-12.82,Interruption 28,-12.23,Interruption 29,-11.28,Interruption 30,-9.99,Interruption 31,-8.39,Interruption 32,-6.53,Interruption 33,-4.48,Interruption 34,-2.29,Interruption 1,1.69,Interruption 2,3.33,Interruption 3,4.87,Interruption 4,6.26,Interruption 5,7.47,Interruption 6,8.44,Interruption 7,9.16,Interruption 8,9.6,Interruption 9,9.75,Interruption 10,9.6,Interruption 11,9.16,Interruption 12,8.45,Interruption 13,7.48,Interruption 14,6.27,Interruption 15,4.88,Interruption 16,3.35,Interruption 17,1.71,Interruption 18,-1.68,Interruption 19,-3.32,Interruption 20,-4.86,Interruption 21,-6.25,Interruption 22,-7.46,Interruption 23,-8.44,Interruption 24,-9.16,Interruption 25,-9.6,Interruption 26,-9.75,Interruption 27,-9.61,Interruption 28,-9.17,Interruption 29,-8.45,Interruption 30,-7.48,Interruption 31,-6.28,Interruption 32,-4.9,Interruption 33,-3.36,Interruption 34,-1.72,Interruption 1,1.41,Interruption 2,2.78,Interruption 3,4.06,Interruption 4,5.22,Interruption 5,6.22,Interruption 6,7.03,Interruption 7,7.63,Interruption 8,8,Interruption 9,8.12,Interruption 10,8,Interruption 11,7.64,Interruption 12,7.04,Interruption 13,6.23,Interruption 14,5.23,Interruption 15,4.07,Interruption 16,2.79,Interruption 17,1.42,Interruption 18,-1.4,Interruption 19,-2.77,Interruption 20,-4.05,Interruption 21,-5.21,Interruption 22,-6.22,Interruption 23,-7.03,Interruption 24,-7.63,Interruption 25,-8,Interruption 26,-8.12,Interruption 27,-8,Interruption 28,-7.64,Interruption 29,-7.05,Interruption 30,-6.24,Interruption 31,-5.24,Interruption 32,-4.08,Interruption 33,-2.8,Interruption 34,-1.43,Interruption 1,1.13,Interruption 2,2.23,Interruption 3,3.25,Interruption 4,4.18,Interruption 5,4.99,Interruption 6,5.64,Interruption 7,6.12,Interruption 8,6.41,Interruption 9,6.51,Interruption 10,6.41,Interruption 11,6.12,Interruption 12,5.64,Interruption 13,4.99,Interruption 14,4.19,Interruption 15,3.26,Interruption 16,2.23,Interruption 17,1.14,Interruption 18,-1.12,Interruption 19,-2.22,Interruption 20,-3.25,Interruption 21,-4.18,Interruption 22,-4.98,Interruption 23,-5.63,Interruption 24,-6.11,Interruption 25,-6.41,Interruption 26,-6.51,Interruption 27,-6.41,Interruption 28,-6.12,Interruption 29,-5.65,Interruption 30,-5,Interruption 31,-4.2,Interruption 32,-3.27,Interruption 33,-2.24,Interruption 34,-1.15,Interruption 1,0.56,Interruption 2,1.11,Interruption 3,1.62,Interruption 4,2.09,Interruption 5,2.49,Interruption 6,2.81,Interruption 7,3.05,Interruption 8,3.2,Interruption 9,3.25,Interruption 10,3.2,Interruption 11,3.05,Interruption 12,2.82,Interruption 13,2.49,Interruption 14,2.09,Interruption 15,1.63,Interruption 16,1.12,Interruption 17,0.57,Interruption 18,-0.56,Interruption 19,-1.11,Interruption 20,-1.62,Interruption 21,-2.08,Interruption 22,-2.49,Interruption 23,-2.81,Interruption 24,-3.05,Interruption 25,-3.2,Interruption 26,-3.25,Interruption 27,-3.2,Interruption 28,-3.06,Interruption 29,-2.82,Interruption 30,-2.49,Interruption 31,-2.09,Interruption 32,-1.63,Interruption 33,-1.12,Interruption 34,-0.57,Interruption 1,0.35,Interruption 2,0.68,Interruption 3,1,Interruption 4,1.29,Interruption 5,1.53,Interruption 6,1.73,Interruption 7,1.88,Interruption 8,1.97,Interruption 9,2,Interruption 10,1.97,Interruption 11,1.88,Interruption 12,1.73,Interruption 13,1.53,Interruption 14,1.29,Interruption 15,1,Interruption 16,0.69,Interruption 17,0.35,Interruption 18,-0.34,Interruption 19,-0.68,Interruption 20,-1,Interruption 21,-1.28,Interruption 22,-1.53,Interruption 23,-1.73,Interruption 24,-1.88,Interruption 25,-1.97,Interruption 26,-2,Interruption 27,-1.97,Interruption 28,-1.88,Interruption 29,-1.73,Interruption 30,-1.54,Interruption 31,-1.29,Interruption 32,-1,Interruption 33,-0.69,Interruption 34,-0.35,Interruption 1,0.17,Interruption 2,0.34,Interruption 3,0.5,Interruption 4,0.64,Interruption 5,0.77,Interruption 6,0.87,Interruption 7,0.94,Interruption 8,0.98,Interruption 9,1,Interruption 10,0.98,Interruption 11,0.94,Interruption 12,0.87,Interruption 13,0.77,Interruption 14,0.64,Interruption 15,0.5,Interruption 16,0.34,Interruption 17,0.17,Interruption 18,-0.17,Interruption 19,-0.34,Interruption 20,-0.5,Interruption 21,-0.64,Interruption 22,-0.76,Interruption 23,-0.87,Interruption 24,-0.94,Interruption 25,-0.98,Interruption 26,-1,Interruption 27,-0.99,Interruption 28,-0.94,Interruption 29,-0.87,Interruption 30,-0.77,Interruption 31,-0.64,Interruption 32,-0.5,Interruption 33,-0.34,Interruption 34,-0.18,Interruption 1,0.09,Interruption 2,0.17,Interruption 3,0.25,Interruption 4,0.32,Interruption 5,0.38,Interruption 6,0.43,Interruption 7,0.47,Interruption 8,0.49,Interruption 9,0.5,Interruption 10,0.49,Interruption 11,0.47,Interruption 12,0.43,Interruption 13,0.38,Interruption 14,0.32,Interruption 15,0.25,Interruption 16,0.17,Interruption 17,0.09,Interruption 18,-0.09,Interruption 19,-0.17,Interruption 20,-0.25,Interruption 21,-0.32,Interruption 22,-0.38,Interruption 23,-0.43,Interruption 24,-0.47,Interruption 25,-0.49,Interruption 26,-0.5,Interruption 27,-0.49,Interruption 28,-0.47,Interruption 29,-0.43,Interruption 30,-0.38,Interruption 31,-0.32,Interruption 32,-0.25,Interruption 33,-0.17,Interruption 34,-0.09,Interruption 1,204.16,Harmonics 2,299.1,Harmonics 3,280.44,Harmonics 4,235,Harmonics 5,234.09,Harmonics 6,265.48,Harmonics 7,275.77,Harmonics 8,252.48,Harmonics 9,235.48,Harmonics 10,252.26,Harmonics 11,275.69,Harmonics 12,265.7,Harmonics 13,234.27,Harmonics 14,234.78,Harmonics 15,280.06,Harmonics 16,299.32,Harmonics 17,205.4,Harmonics 18,-202.92,Harmonics 19,-298.88,Harmonics 20,-280.81,Harmonics 21,-235.22,Harmonics 22,-233.91,Harmonics 23,-265.26,Harmonics 24,-275.84,Harmonics 25,-252.7,Harmonics 26,-235.48,Harmonics 27,-252.04,Harmonics 28,-275.6,Harmonics 29,-265.92,Harmonics 30,-234.46,Harmonics 31,-234.56,Harmonics 32,-279.68,Harmonics 33,-299.53,Harmonics 34,-206.62,Harmonics 1,214.5,Harmonics 2,312.26,Harmonics 3,288.69,Harmonics 4,236.81,Harmonics 5,233.04,Harmonics 6,264.35,Harmonics 7,273.68,Harmonics 8,247.73,Harmonics 9,229.19,Harmonics 10,247.49,Harmonics 11,273.58,Harmonics 12,264.57,Harmonics 13,233.21,Harmonics 14,236.56,Harmonics 15,288.25,Harmonics 16,312.46,Harmonics 17,215.79,Harmonics 18,-213.2,Harmonics 19,-312.05,Harmonics 20,-289.12,Harmonics 21,-237.07,Harmonics 22,-232.86,Harmonics 23,-264.14,Harmonics 24,-273.77,Harmonics 25,-247.97,Harmonics 26,-229.19,Harmonics 27,-247.26,Harmonics 28,-273.48,Harmonics 29,-264.79,Harmonics 30,-233.39,Harmonics 31,-236.31,Harmonics 32,-287.82,Harmonics 33,-312.65,Harmonics 34,-217.08,Harmonics 1,213.02,Harmonics 2,310.38,Harmonics 3,287.51,Harmonics 4,236.55,Harmonics 5,233.19,Harmonics 6,264.52,Harmonics 7,273.98,Harmonics 8,248.41,Harmonics 9,230.09,Harmonics 10,248.17,Harmonics 11,273.88,Harmonics 12,264.73,Harmonics 13,233.37,Harmonics 14,236.3,Harmonics 15,287.08,Harmonics 16,310.58,Harmonics 17,214.31,Harmonics 18,-211.73,Harmonics 19,-310.17,Harmonics 20,-287.93,Harmonics 21,-236.81,Harmonics 22,-233.01,Harmonics 23,-264.3,Harmonics 24,-274.07,Harmonics 25,-248.65,Harmonics 26,-230.09,Harmonics 27,-247.94,Harmonics 28,-273.79,Harmonics 29,-264.95,Harmonics 30,-233.55,Harmonics 31,-236.06,Harmonics 32,-286.66,Harmonics 33,-310.78,Harmonics 34,-215.58,Harmonics 1,195.3,Harmonics 2,287.83,Harmonics 3,273.36,Harmonics 4,233.44,Harmonics 5,234.99,Harmonics 6,266.45,Harmonics 7,277.56,Harmonics 8,256.55,Harmonics 9,240.86,Harmonics 10,256.35,Harmonics 11,277.49,Harmonics 12,266.67,Harmonics 13,235.18,Harmonics 14,233.25,Harmonics 15,273.03,Harmonics 16,288.06,Harmonics 17,196.49,Harmonics 18,-194.11,Harmonics 19,-287.59,Harmonics 20,-273.7,Harmonics 21,-233.62,Harmonics 22,-234.8,Harmonics 23,-266.23,Harmonics 24,-277.62,Harmonics 25,-256.75,Harmonics 26,-240.87,Harmonics 27,-256.15,Harmonics 28,-277.42,Harmonics 29,-266.89,Harmonics 30,-235.37,Harmonics 31,-233.07,Harmonics 32,-272.7,Harmonics 33,-288.28,Harmonics 34,-197.67,Harmonics 1,193.82,Harmonics 2,285.95,Harmonics 3,272.19,Harmonics 4,233.18,Harmonics 5,235.14,Harmonics 6,266.61,Harmonics 7,277.85,Harmonics 8,257.23,Harmonics 9,241.76,Harmonics 10,257.03,Harmonics 11,277.79,Harmonics 12,266.83,Harmonics 13,235.33,Harmonics 14,233,Harmonics 15,271.86,Harmonics 16,286.18,Harmonics 17,195,Harmonics 18,-192.64,Harmonics 19,-285.71,Harmonics 20,-272.51,Harmonics 21,-233.36,Harmonics 22,-234.95,Harmonics 23,-266.39,Harmonics 24,-277.91,Harmonics 25,-257.42,Harmonics 26,-241.76,Harmonics 27,-256.83,Harmonics 28,-277.72,Harmonics 29,-267.05,Harmonics 30,-235.52,Harmonics 31,-232.82,Harmonics 32,-271.53,Harmonics 33,-286.4,Harmonics 34,-196.17,Harmonics 1,192.35,Harmonics 2,284.07,Harmonics 3,271.01,Harmonics 4,232.92,Harmonics 5,235.29,Harmonics 6,266.78,Harmonics 7,278.15,Harmonics 8,257.9,Harmonics 9,242.66,Harmonics 10,257.71,Harmonics 11,278.09,Harmonics 12,266.99,Harmonics 13,235.48,Harmonics 14,232.74,Harmonics 15,270.69,Harmonics 16,284.3,Harmonics 17,193.52,Harmonics 18,-191.17,Harmonics 19,-283.83,Harmonics 20,-271.32,Harmonics 21,-233.09,Harmonics 22,-235.1,Harmonics 23,-266.56,Harmonics 24,-278.21,Harmonics 25,-258.1,Harmonics 26,-242.66,Harmonics 27,-257.52,Harmonics 28,-278.03,Harmonics 29,-267.21,Harmonics 30,-235.67,Harmonics 31,-232.57,Harmonics 32,-270.37,Harmonics 33,-284.53,Harmonics 34,-194.68,Harmonics 1,190.87,Harmonics 2,282.19,Harmonics 3,269.83,Harmonics 4,232.66,Harmonics 5,235.44,Harmonics 6,266.94,Harmonics 7,278.45,Harmonics 8,258.58,Harmonics 9,243.56,Harmonics 10,258.39,Harmonics 11,278.39,Harmonics 12,267.15,Harmonics 13,235.63,Harmonics 14,232.49,Harmonics 15,269.52,Harmonics 16,282.42,Harmonics 17,192.03,Harmonics 18,-189.7,Harmonics 19,-281.95,Harmonics 20,-270.14,Harmonics 21,-232.83,Harmonics 22,-235.25,Harmonics 23,-266.72,Harmonics 24,-278.51,Harmonics 25,-258.77,Harmonics 26,-243.56,Harmonics 27,-258.2,Harmonics 28,-278.33,Harmonics 29,-267.37,Harmonics 30,-235.82,Harmonics 31,-232.32,Harmonics 32,-269.21,Harmonics 33,-282.65,Harmonics 34,-193.19,Harmonics 1,202.69,Harmonics 2,297.22,Harmonics 3,279.26,Harmonics 4,234.74,Harmonics 5,234.24,Harmonics 6,265.65,Harmonics 7,276.06,Harmonics 8,253.16,Harmonics 9,236.37,Harmonics 10,252.94,Harmonics 11,275.99,Harmonics 12,265.86,Harmonics 13,234.42,Harmonics 14,234.52,Harmonics 15,278.89,Harmonics 16,297.44,Harmonics 17,203.91,Harmonics 18,-201.45,Harmonics 19,-297,Harmonics 20,-279.63,Harmonics 21,-234.95,Harmonics 22,-234.06,Harmonics 23,-265.43,Harmonics 24,-276.14,Harmonics 25,-253.37,Harmonics 26,-236.38,Harmonics 27,-252.73,Harmonics 28,-275.91,Harmonics 29,-266.08,Harmonics 30,-234.61,Harmonics 31,-234.31,Harmonics 32,-278.51,Harmonics 33,-297.65,Harmonics 34,-205.13,Harmonics 1,201.21,Harmonics 2,295.34,Harmonics 3,278.08,Harmonics 4,234.48,Harmonics 5,234.39,Harmonics 6,265.81,Harmonics 7,276.36,Harmonics 8,253.84,Harmonics 9,237.27,Harmonics 10,253.62,Harmonics 11,276.29,Harmonics 12,266.03,Harmonics 13,234.57,Harmonics 14,234.27,Harmonics 15,277.71,Harmonics 16,295.56,Harmonics 17,202.43,Harmonics 18,-199.98,Harmonics 19,-295.12,Harmonics 20,-278.44,Harmonics 21,-234.68,Harmonics 22,-234.2,Harmonics 23,-265.59,Harmonics 24,-276.43,Harmonics 25,-254.05,Harmonics 26,-237.27,Harmonics 27,-253.41,Harmonics 28,-276.21,Harmonics 29,-266.24,Harmonics 30,-234.76,Harmonics 31,-234.07,Harmonics 32,-277.35,Harmonics 33,-295.78,Harmonics 34,-203.64,Harmonics 1,199.73,Harmonics 2,293.47,Harmonics 3,276.9,Harmonics 4,234.22,Harmonics 5,234.54,Harmonics 6,265.97,Harmonics 7,276.66,Harmonics 8,254.51,Harmonics 9,238.17,Harmonics 10,254.3,Harmonics 11,276.59,Harmonics 12,266.19,Harmonics 13,234.72,Harmonics 14,234.01,Harmonics 15,276.54,Harmonics 16,293.69,Harmonics 17,200.94,Harmonics 18,-198.51,Harmonics 19,-293.24,Harmonics 20,-277.25,Harmonics 21,-234.42,Harmonics 22,-234.35,Harmonics 23,-265.75,Harmonics 24,-276.73,Harmonics 25,-254.72,Harmonics 26,-238.17,Harmonics 27,-254.1,Harmonics 28,-276.51,Harmonics 29,-266.4,Harmonics 30,-234.91,Harmonics 31,-233.82,Harmonics 32,-276.19,Harmonics 33,-293.9,Harmonics 34,-202.14,Harmonics 1,198.25,Harmonics 2,291.59,Harmonics 3,275.72,Harmonics 4,233.96,Harmonics 5,234.69,Harmonics 6,266.13,Harmonics 7,276.96,Harmonics 8,255.19,Harmonics 9,239.07,Harmonics 10,254.99,Harmonics 11,276.89,Harmonics 12,266.35,Harmonics 13,234.88,Harmonics 14,233.76,Harmonics 15,275.37,Harmonics 16,291.81,Harmonics 17,199.46,Harmonics 18,-197.05,Harmonics 19,-291.36,Harmonics 20,-276.07,Harmonics 21,-234.15,Harmonics 22,-234.5,Harmonics 23,-265.91,Harmonics 24,-277.03,Harmonics 25,-255.4,Harmonics 26,-239.07,Harmonics 27,-254.78,Harmonics 28,-276.82,Harmonics 29,-266.56,Harmonics 30,-235.06,Harmonics 31,-233.57,Harmonics 32,-275.02,Harmonics 33,-292.03,Harmonics 34,-200.65,Harmonics 1,196.78,Harmonics 2,289.71,Harmonics 3,274.54,Harmonics 4,233.7,Harmonics 5,234.84,Harmonics 6,266.29,Harmonics 7,277.26,Harmonics 8,255.87,Harmonics 9,239.97,Harmonics 10,255.67,Harmonics 11,277.19,Harmonics 12,266.51,Harmonics 13,235.03,Harmonics 14,233.51,Harmonics 15,274.2,Harmonics 16,289.93,Harmonics 17,197.97,Harmonics 18,-195.58,Harmonics 19,-289.48,Harmonics 20,-274.88,Harmonics 21,-233.89,Harmonics 22,-234.65,Harmonics 23,-266.07,Harmonics 24,-277.32,Harmonics 25,-256.07,Harmonics 26,-239.97,Harmonics 27,-255.46,Harmonics 28,-277.12,Harmonics 29,-266.73,Harmonics 30,-235.22,Harmonics 31,-233.32,Harmonics 32,-273.86,Harmonics 33,-290.15,Harmonics 34,-199.16,Harmonics 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# 归一化处理 + X = (X - np.min(X)) / (np.max(X) - np.min(X)) + + # 转换为时间序列数据格式 + time_steps = 34 + X_series, Y_series = [], [] + for i in range(0, len(X) - time_steps): + X_series.append(X[i:(i + time_steps)]) + Y_series.append(Y[i + time_steps - 1]) + + return np.array(X_series).reshape(-1, time_steps, 1), np.array(Y_series) + + +X_train, Y_train = data_read( + 'Liu\data\VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main\Voltage Quality.csv') +X_test, Y_test = data_read( + 'Liu/data/VOLTAGE-QUALITY-CLASSIFICATION-MODEL--main/Voltage Quality Test.csv') + +# 获取类别数量 +n_classes = len(np.unique(Y_train)) + +# 构建模型 +model = tf.keras.models.Sequential([ + tf.keras.layers.LSTM(50, return_sequences=True, input_shape=(34, 1)), + tf.keras.layers.LSTM(50), + tf.keras.layers.Dense(n_classes, activation='softmax') # 修改为适应多分类 +]) + +# 编译模型 +model.compile(optimizer='adam', + loss='sparse_categorical_crossentropy', metrics=['accuracy']) + +# 训练模型 +model.fit(X_train, Y_train, epochs=3000, validation_split=0.2) + +# 评估模型 +loss, accuracy = model.evaluate(X_test, Y_test) + + +# 制作扰动数据 + +# 损失函数 +loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) + +# 定义损失函数 +loss_fn = tf.keras.losses.SparseCategoricalCrossentropy() + +# 转换X_train和Y_train为TensorFlow张量 +X_train_tensor = tf.convert_to_tensor(X_train, dtype=tf.float32) +Y_train_tensor = tf.convert_to_tensor(Y_train, dtype=tf.int32) + +# 使用tf.GradientTape来计算梯度 +with tf.GradientTape() as tape: + # 确保tape监视输入张量 + tape.watch(X_train_tensor) + # 前向传播，计算预测值 + predictions = model(X_train_tensor) + # 计算损失 + loss = loss_fn(Y_train_tensor, predictions) + +# 计算关于输入X的梯度 +gradients = tape.gradient(loss, X_train_tensor) + +# 计算每个输入的梯度的L2范数 +gradient_magnitudes = tf.norm(gradients, axis=1) + +# 创建每个gamma对应的准确率的字典 +accuracy_per_gamma = {} + +# 选择最大的γ * |X|个梯度 +for gamma in [0.05, 0.1, 0.2, 0.4]: # 你需要选择一个合适的γ值 + num_gradients_to_select = int( + gamma * tf.size(gradient_magnitudes, out_type=tf.dtypes.float32)) + + # 获取最大梯度的索引 + # tf.argsort返回的是升序排列的，所以用[::-1]来获得降序的索引 + top_gradients_indices = tf.argsort(gradient_magnitudes, direction='DESCENDING')[ + :num_gradients_to_select] + + # 创建集合A，这里是所有选定的最大梯度的索引 + A = top_gradients_indices.numpy() + + # 创建一个新的梯度张量，初始化为原始梯度的副本 + updated_gradients = tf.identity(gradients) + + # 获取所有索引 + all_indices = tf.range(start=0, limit=tf.size( + gradient_magnitudes, out_type=tf.dtypes.int32), dtype=tf.int32) + + # 创建一个布尔掩码，其中集合A中的索引为False，其他为True + mask = ~tf.reduce_any(tf.equal(tf.expand_dims( + all_indices, 1), tf.reshape(A, (1, -1))), axis=1) + + # 使用这个掩码更新不在集合A中的梯度为0 + updated_gradients = tf.where( + mask, updated_gradients, tf.zeros_like(updated_gradients)) + + # 创建准确率列表 + accuracy_list = [] + + for learning_rate in [0.1, 0.2, 0.3, 0.4, 0.5]: + + # 更新X_train_tensor + X_train_updated = X_train_tensor - updated_gradients + + # 编译模型 + model.compile( + optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) + + # 训练模型 + model.fit(X_train, Y_train, epochs=3000, validation_split=0.2) + + # 评估模型 + loss, accuracy = model.evaluate(X_test, Y_test) + + # 记录准确率 + accuracy_list.append(accuracy) + + # 记录该gamma下的准确率 + accuracy_per_gamma[gamma] = accuracy_list + +# 学习率样本 +learning_rates = [0.1, 0.2, 0.3, 0.4, 0.5] + +# 不同的gamma值 +gammas = [0.05, 0.1, 0.2, 0.4] + +# 创建图像 +plt.figure(figsize=(10, 6)) + +# 为每个gamma值绘制曲线 +for gamma in gammas: + plt.plot(learning_rates, accuracy_per_gamma[gamma], marker='o', label=f'Gamma={gamma}') + +# 添加标题和标签 +plt.title('Accuracy vs Learning Rate for Different Gammas') +plt.xlabel('Learning Rate') +plt.ylabel('Accuracy') +plt.legend() + +# 显示图像 +plt.show() +