{ "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" ] } ] } ] }