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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "sBCf6C09cb6Q"
},
"outputs": [],
"source": [
"from prettytable import PrettyTable"
]
},
{
"cell_type": "code",
"source": [
"ptable1 = PrettyTable()\n",
"ptable1.title = \" Model Comparision \"\n",
"ptable1.field_names = ['Model Name','Hyperparameter Tunning', 'Accuracy']\n",
"\n",
"print(\"\\n\\n ********** Machine Learning Model Comparision ************\")\n",
"ptable1.add_row([\"Logistic Regression\",\"Done\",\"95.83%\"])\n",
"ptable1.add_row([\"Linear SVC \",\"Done\",\"96.74%\"])\n",
"ptable1.add_row([\"rbf SVM classifier\",\"Done\",\"96.27%\"])\n",
"ptable1.add_row([\"DecisionTree\",\"Done\",\"87.78%\"])\n",
"ptable1.add_row([\"Random Forest\",\"Done\",\"92.67%\"])\n",
"\n",
"print(ptable1)\n",
"# *****************************************************************\n",
"\n",
"ptable2 = PrettyTable()\n",
"ptable2.title = \" Model Comparision \"\n",
"ptable2.field_names = ['Model Name','Hyperparameter Tunning', 'categorical_crossentropy', 'Accuracy']\n",
"\n",
"print(\"\\n\\n ********************************* Deep Learning LSTM Model Comparision ***********************************\")\n",
"ptable2.add_row([\"LSTM With 1_Layer(neurons:32)\",\"Done\",\"0.47\", \"0.91\"])\n",
"ptable2.add_row([\"LSTM With 2_Layer(neurons:48, neurons:32)\",\"Done\",\"0.39\", \"0.91\"])\n",
"ptable2.add_row([\"LSTM With 2_Layer(neurons:64, neurons:48)\",\"Done\",\"0.27\", \"0.91\"])\n",
"\n",
"print(ptable2)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "RwKBoh7lfHtY",
"outputId": "d04e7c3a-c526-413d-f3fa-4625f2442b98"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"\n",
" ********** Machine Learning Model Comparision ************\n",
"+---------------------------------------------------------+\n",
"| Model Comparision |\n",
"+---------------------+------------------------+----------+\n",
"| Model Name | Hyperparameter Tunning | Accuracy |\n",
"+---------------------+------------------------+----------+\n",
"| Logistic Regression | Done | 95.83% |\n",
"| Linear SVC | Done | 96.74% |\n",
"| rbf SVM classifier | Done | 96.27% |\n",
"| DecisionTree | Done | 87.78% |\n",
"| Random Forest | Done | 92.67% |\n",
"+---------------------+------------------------+----------+\n",
"\n",
"\n",
" ********************************* Deep Learning LSTM Model Comparision ***********************************\n",
"+----------------------------------------------------------------------------------------------------------+\n",
"| Model Comparision |\n",
"+-------------------------------------------+------------------------+--------------------------+----------+\n",
"| Model Name | Hyperparameter Tunning | categorical_crossentropy | Accuracy |\n",
"+-------------------------------------------+------------------------+--------------------------+----------+\n",
"| LSTM With 1_Layer(neurons:32) | Done | 0.47 | 0.92 |\n",
"| LSTM With 2_Layer(neurons:48, neurons:32) | Done | 0.39 | 0.89 |\n",
"| LSTM With 2_Layer(neurons:64, neurons:48) | Done | 0.27 | 0.91 |\n",
"+-------------------------------------------+------------------------+--------------------------+----------+\n"
]
}
]
}
]
} |