{ "cells": [ { "cell_type": "markdown", "id": "a29a237f", "metadata": {}, "source": [ "## Name : ADVAIT GURUNATH CHAVAN\n", "## Contact Number : +91 70214 55852\n", "## Mail ID :advaitchavan135@gmail.com \n", "\n", "\n", "## Oasis Infobyte Data Science Intern\n", "## Task 4 : Email Mail Spam Detection with Machine Learning." ] }, { "cell_type": "markdown", "id": "b4a25e6b", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "id": "04b36837", "metadata": {}, "source": [ "### 1. Importing the necessary dependencies " ] }, { "cell_type": "code", "execution_count": 1, "id": "9ba9aceb", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import plotly.io as plio\n", "plio.templates\n", "import seaborn as sns\n", "import plotly.express as px\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.feature_extraction.text import CountVectorizer\n", "from sklearn.naive_bayes import MultinomialNB\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.svm import SVC\n", "import joblib\n", "import re\n", "from sklearn.metrics import confusion_matrix, accuracy_score, classification_report,precision_recall_curve, average_precision_score\n", "from warnings import filterwarnings\n", "filterwarnings(action='ignore')" ] }, { "cell_type": "markdown", "id": "c9decead", "metadata": {}, "source": [ "### 2. Exploring the dataset" ] }, { "cell_type": "code", "execution_count": 2, "id": "2fe76627", "metadata": {}, "outputs": [], "source": [ "data = pd.read_csv('spam.csv', encoding='ISO-8859-1')" ] }, { "cell_type": "code", "execution_count": 3, "id": "526a314a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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v1v2Unnamed: 2Unnamed: 3Unnamed: 4
0hamGo until jurong point, crazy.. Available only ...NaNNaNNaN
1hamOk lar... Joking wif u oni...NaNNaNNaN
2spamFree entry in 2 a wkly comp to win FA Cup fina...NaNNaNNaN
3hamU dun say so early hor... U c already then say...NaNNaNNaN
4hamNah I don't think he goes to usf, he lives aro...NaNNaNNaN
..................
5567spamThis is the 2nd time we have tried 2 contact u...NaNNaNNaN
5568hamWill Ì_ b going to esplanade fr home?NaNNaNNaN
5569hamPity, * was in mood for that. So...any other s...NaNNaNNaN
5570hamThe guy did some bitching but I acted like i'd...NaNNaNNaN
5571hamRofl. Its true to its nameNaNNaNNaN
\n", "

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" ], "text/plain": [ " v1 v2 Unnamed: 2 \\\n", "0 ham Go until jurong point, crazy.. Available only ... NaN \n", "1 ham Ok lar... Joking wif u oni... NaN \n", "2 spam Free entry in 2 a wkly comp to win FA Cup fina... NaN \n", "3 ham U dun say so early hor... U c already then say... NaN \n", "4 ham Nah I don't think he goes to usf, he lives aro... NaN \n", "... ... ... ... \n", "5567 spam This is the 2nd time we have tried 2 contact u... NaN \n", "5568 ham Will Ì_ b going to esplanade fr home? NaN \n", "5569 ham Pity, * was in mood for that. So...any other s... NaN \n", "5570 ham The guy did some bitching but I acted like i'd... NaN \n", "5571 ham Rofl. Its true to its name NaN \n", "\n", " Unnamed: 3 Unnamed: 4 \n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "... ... ... \n", "5567 NaN NaN \n", "5568 NaN NaN \n", "5569 NaN NaN \n", "5570 NaN NaN \n", "5571 NaN NaN \n", "\n", "[5572 rows x 5 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "code", "execution_count": 4, "id": "8c6d23d6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 5572 entries, 0 to 5571\n", "Data columns (total 5 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 v1 5572 non-null object\n", " 1 v2 5572 non-null object\n", " 2 Unnamed: 2 50 non-null object\n", " 3 Unnamed: 3 12 non-null object\n", " 4 Unnamed: 4 6 non-null object\n", "dtypes: object(5)\n", "memory usage: 217.8+ KB\n" ] } ], "source": [ "data.info()" ] }, { "cell_type": "markdown", "id": "659e458a", "metadata": {}, "source": [ "#### Dropping unnecessary columns from the dataset" ] }, { "cell_type": "code", "execution_count": 5, "id": "56b9d4fd", "metadata": {}, "outputs": [], "source": [ "columns_to_drop = ['Unnamed: 2', 'Unnamed: 3','Unnamed: 4']\n", "data.drop(columns=columns_to_drop, inplace=True)" ] }, { "cell_type": "code", "execution_count": 6, "id": "e949c9f6", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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v1v2
0hamGo until jurong point, crazy.. Available only ...
1hamOk lar... Joking wif u oni...
2spamFree entry in 2 a wkly comp to win FA Cup fina...
3hamU dun say so early hor... U c already then say...
4hamNah I don't think he goes to usf, he lives aro...
.........
5567spamThis is the 2nd time we have tried 2 contact u...
5568hamWill Ì_ b going to esplanade fr home?
5569hamPity, * was in mood for that. So...any other s...
5570hamThe guy did some bitching but I acted like i'd...
5571hamRofl. Its true to its name
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classtext
0hamGo until jurong point, crazy.. Available only ...
1hamOk lar... Joking wif u oni...
2spamFree entry in 2 a wkly comp to win FA Cup fina...
3hamU dun say so early hor... U c already then say...
4hamNah I don't think he goes to usf, he lives aro...
.........
5567spamThis is the 2nd time we have tried 2 contact u...
5568hamWill Ì_ b going to esplanade fr home?
5569hamPity, * was in mood for that. So...any other s...
5570hamThe guy did some bitching but I acted like i'd...
5571hamRofl. Its true to its name
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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Count the occurrences of top 15 unique strings in the 'text' column\n", "value_counts = data['text'].value_counts().head(15).reset_index()\n", "value_counts.columns = ['Category', 'Count']\n", "\n", "# Create a bar plot using Plotly\n", "fig = px.bar(value_counts, x='Category', y='Count')\n", "\n", "# Add values to the bars\n", "fig.update_traces(texttemplate='%{y}', textposition='outside')\n", "\n", "# Set plot labels and title\n", "fig.update_xaxes(title='text')\n", "fig.update_yaxes(title='Occurences of the text')\n", "fig.update_layout(title='Most Common String in the Text Column')\n", "\n", "# Show the plot\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "018f1446", "metadata": {}, "source": [ "#### Encoding the class column " ] }, { "cell_type": "code", "execution_count": 11, "id": "6017d549", "metadata": {}, "outputs": [], "source": [ "# Changing Class column : ham -> 0, spam -> 1\n", "category_mapping = {'ham': 0, 'spam': 1}\n", "data['class'] = data['class'].map(category_mapping)" ] }, { "cell_type": "code", "execution_count": 12, "id": "f99732de", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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classtext
00Go until jurong point, crazy.. Available only ...
10Ok lar... Joking wif u oni...
21Free entry in 2 a wkly comp to win FA Cup fina...
30U dun say so early hor... U c already then say...
40Nah I don't think he goes to usf, he lives aro...
.........
55671This is the 2nd time we have tried 2 contact u...
55680Will Ì_ b going to esplanade fr home?
55690Pity, * was in mood for that. So...any other s...
55700The guy did some bitching but I acted like i'd...
55710Rofl. Its true to its name
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" ], "text/plain": [ " class text\n", "0 0 Go until jurong point, crazy.. Available only ...\n", "1 0 Ok lar... Joking wif u oni...\n", "2 1 Free entry in 2 a wkly comp to win FA Cup fina...\n", "3 0 U dun say so early hor... U c already then say...\n", "4 0 Nah I don't think he goes to usf, he lives aro...\n", "... ... ...\n", "5567 1 This is the 2nd time we have tried 2 contact u...\n", "5568 0 Will Ì_ b going to esplanade fr home?\n", "5569 0 Pity, * was in mood for that. So...any other s...\n", "5570 0 The guy did some bitching but I acted like i'd...\n", "5571 0 Rofl. Its true to its name\n", "\n", "[5572 rows x 2 columns]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "markdown", "id": "efaf12e4", "metadata": {}, "source": [ "### 3. Data Modelling (Preparing the training and testing data)" ] }, { "cell_type": "code", "execution_count": 13, "id": "b50d97a3", "metadata": {}, "outputs": [], "source": [ "x_train, x_test, y_train, y_test=train_test_split(data.text, data['class'],test_size=0.3)" ] }, { "cell_type": "code", "execution_count": 14, "id": "4866fb7d", "metadata": {}, "outputs": [], "source": [ "#x_train.to_csv('x_train.csv',index = False)\n", "#x_test.to_csv('x_test.csv', index=False)\n", "#y_train.to_csv('y_train.csv', index=False)\n", "#y_test.to_csv('y_test.csv',index=False)" ] }, { "cell_type": "markdown", "id": "9d3131af", "metadata": {}, "source": [ "### 4. Countervectorizing x_train and x_test" ] }, { "cell_type": "markdown", "id": "f34eca08", "metadata": {}, "source": [ "#### CountVectorizer is commonly used in text classification tasks, where it helps convert text strings into a format suitable for training classifiers." ] }, { "cell_type": "code", "execution_count": 15, "id": "bd5f5d63", "metadata": {}, "outputs": [], "source": [ "#x_train = pd.read_csv('x_train.csv')\n", "#x_test = pd.read_csv('x_test.csv')\n", "#y_train = pd.read_csv('y_train.csv')\n", "#y_test = pd.read_csv('y_test.csv')" ] }, { "cell_type": "code", "execution_count": 16, "id": "d15b68e8", "metadata": {}, "outputs": [], "source": [ "cv = CountVectorizer()" ] }, { "cell_type": "code", "execution_count": 17, "id": "fe3f09db", "metadata": {}, "outputs": [], "source": [ "x_train_new = cv.fit_transform(x_train)" ] }, { "cell_type": "code", "execution_count": 18, "id": "06d32de7", "metadata": {}, "outputs": [], "source": [ "x_test_new = cv.transform(x_test)" ] }, { "cell_type": "code", "execution_count": 19, "id": "9308cd9c", "metadata": {}, "outputs": [], "source": [ "x_train_array = x_train_new.toarray()\n", "x_test_array = x_test_new.toarray()" ] }, { "cell_type": "markdown", "id": "83283e7e", "metadata": {}, "source": [ "### 5. Training and testing using Classification Models\n", "\n", "\n", "### [A] Multinomial Naive Bayes Classifier" ] }, { "cell_type": "code", "execution_count": 20, "id": "47a9d0a2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "MultinomialNB()" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "classifier_1 = MultinomialNB()\n", "classifier_1.fit(x_train_new, y_train)" ] }, { "cell_type": "code", "execution_count": 21, "id": "b7910f24", "metadata": {}, "outputs": [], "source": [ "y_pred_1 = classifier_1.predict(x_test_new)" ] }, { "cell_type": "code", "execution_count": 22, "id": "345c7e3d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Confusion Matrix:\n", "[[1424 6]\n", " [ 18 224]]\n" ] } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_1)\n", "print(\"Confusion Matrix:\")\n", "print(conf_matrix)" ] }, { "cell_type": "code", "execution_count": 23, "id": "4819d0d3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.9856459330143541\n" ] } ], "source": [ "accuracy_1 = accuracy_score(y_test, y_pred_1)\n", "print(\"Accuracy:\", accuracy_1)" ] }, { "cell_type": "code", "execution_count": 24, "id": "f823f24f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Classification Report:\n", " precision recall f1-score support\n", "\n", " 0 0.99 1.00 0.99 1430\n", " 1 0.97 0.93 0.95 242\n", "\n", " accuracy 0.99 1672\n", " macro avg 0.98 0.96 0.97 1672\n", "weighted avg 0.99 0.99 0.99 1672\n", "\n" ] } ], "source": [ "class_report = classification_report(y_test, y_pred_1)\n", "print(\"Classification Report:\")\n", "print(class_report)" ] }, { "cell_type": "code", "execution_count": 25, "id": "70a04757", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_1)\n", "plt.figure(figsize=(8, 6))\n", "plt.imshow(conf_matrix, interpolation='nearest', cmap=plt.get_cmap('Blues'))\n", "plt.title('Confusion Matrix of performance by Multinomial Naive Bayes classifier')\n", "plt.colorbar()\n", "tick_marks = [0, 1] # Assuming binary classification (e.g., 0 for non-spam and 1 for spam)\n", "plt.xticks(tick_marks, ['Predicted Ham(Non-spam)', 'Predicted Spam'], rotation=45)\n", "plt.yticks(tick_marks, ['Actual Ham(Non-spam)', 'Actual Spam'])\n", "plt.tight_layout()\n", "for i in range(2):\n", " for j in range(2):\n", " plt.text(j, i, format(conf_matrix[i, j], 'd'), ha=\"center\", va=\"center\", color=\"white\" if conf_matrix[i, j] > conf_matrix.max() / 2. else \"black\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 26, "id": "546188af", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "precision, recall, _ = precision_recall_curve(y_test, y_pred_1)\n", "average_precision = average_precision_score(y_test, y_pred_1)\n", "plt.figure()\n", "plt.step(recall, precision, color='b', where='post')\n", "plt.fill_between(recall, precision, alpha=0.2, color='r')\n", "plt.xlabel('Recall')\n", "plt.ylabel('Precision')\n", "plt.ylim([0.0, 1.05])\n", "plt.xlim([0.0, 1.0])\n", "plt.title(f'Precision-Recall curve of performance by Multinomial Naive Bayes classifier (Average-precision = {average_precision:.2f})')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "74d599ba", "metadata": {}, "source": [ "### [B] Logistic Regression Classifier" ] }, { "cell_type": "code", "execution_count": 27, "id": "82485b1c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "LogisticRegression()" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "classifier_2 = LogisticRegression()\n", "classifier_2.fit(x_train_new, y_train)" ] }, { "cell_type": "code", "execution_count": 28, "id": "4cf46965", "metadata": {}, "outputs": [], "source": [ "y_pred_2 = classifier_2.predict(x_test_new)" ] }, { "cell_type": "code", "execution_count": 29, "id": "10874a30", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Confusion Matrix:\n", "[[1429 1]\n", " [ 32 210]]\n" ] } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_2)\n", "print(\"Confusion Matrix:\")\n", "print(conf_matrix)" ] }, { "cell_type": "code", "execution_count": 30, "id": "d02f9277", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.9802631578947368\n" ] } ], "source": [ "accuracy_2 = accuracy_score(y_test, y_pred_2)\n", "print(\"Accuracy:\", accuracy_2)" ] }, { "cell_type": "code", "execution_count": 31, "id": "7ca4cbf1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Classification Report:\n", " precision recall f1-score support\n", "\n", " 0 0.98 1.00 0.99 1430\n", " 1 1.00 0.87 0.93 242\n", "\n", " accuracy 0.98 1672\n", " macro avg 0.99 0.93 0.96 1672\n", "weighted avg 0.98 0.98 0.98 1672\n", "\n" ] } ], "source": [ "class_report = classification_report(y_test, y_pred_2)\n", "print(\"Classification Report:\")\n", "print(class_report)" ] }, { "cell_type": "code", "execution_count": 32, "id": "a2f975d1", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_2)\n", "plt.figure(figsize=(8, 6))\n", "plt.imshow(conf_matrix, interpolation='nearest', cmap=plt.get_cmap('Blues'))\n", "plt.title('Confusion Matrix of performance by Logistic Regression classifier')\n", "plt.colorbar()\n", "tick_marks = [0, 1] # Assuming binary classification (e.g., 0 for non-spam and 1 for spam)\n", "plt.xticks(tick_marks, ['Predicted Ham(Non-spam)', 'Predicted Spam'], rotation=45)\n", "plt.yticks(tick_marks, ['Actual Ham(Non-spam)', 'Actual Spam'])\n", "plt.tight_layout()\n", "for i in range(2):\n", " for j in range(2):\n", " plt.text(j, i, format(conf_matrix[i, j], 'd'), ha=\"center\", va=\"center\", color=\"white\" if conf_matrix[i, j] > conf_matrix.max() / 2. else \"black\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 33, "id": "ad39c2d6", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "precision, recall, _ = precision_recall_curve(y_test, y_pred_2)\n", "average_precision = average_precision_score(y_test, y_pred_2)\n", "plt.figure()\n", "plt.step(recall, precision, color='b', where='post')\n", "plt.fill_between(recall, precision, alpha=0.2, color='r')\n", "plt.xlabel('Recall')\n", "plt.ylabel('Precision')\n", "plt.ylim([0.0, 1.05])\n", "plt.xlim([0.0, 1.0])\n", "plt.title(f'Precision-Recall curve of performance by Logistic Regression classifier (Average-precision = {average_precision:.2f})')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "39365020", "metadata": {}, "source": [ "### [C] Decision Tree Classifer" ] }, { "cell_type": "code", "execution_count": 34, "id": "10c6af48", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DecisionTreeClassifier()" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "classifier_3 = DecisionTreeClassifier()\n", "classifier_3.fit(x_train_new, y_train)" ] }, { "cell_type": "code", "execution_count": 35, "id": "7730e8d5", "metadata": {}, "outputs": [], "source": [ "y_pred_3 = classifier_3.predict(x_test_new)" ] }, { "cell_type": "code", "execution_count": 36, "id": "89b8d07a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Confusion Matrix:\n", "[[1409 21]\n", " [ 37 205]]\n" ] } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_3)\n", "print(\"Confusion Matrix:\")\n", "print(conf_matrix)" ] }, { "cell_type": "code", "execution_count": 37, "id": "c52a3801", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.965311004784689\n" ] } ], "source": [ "accuracy_3 = accuracy_score(y_test, y_pred_3)\n", "print(\"Accuracy:\", accuracy_3)" ] }, { "cell_type": "code", "execution_count": 38, "id": "6b4acddc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Classification Report:\n", " precision recall f1-score support\n", "\n", " 0 0.97 0.99 0.98 1430\n", " 1 0.91 0.85 0.88 242\n", "\n", " accuracy 0.97 1672\n", " macro avg 0.94 0.92 0.93 1672\n", "weighted avg 0.96 0.97 0.96 1672\n", "\n" ] } ], "source": [ "class_report = classification_report(y_test, y_pred_3)\n", "print(\"Classification Report:\")\n", "print(class_report)" ] }, { "cell_type": "code", "execution_count": 39, "id": "d686c567", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_3)\n", "plt.figure(figsize=(8, 6))\n", "plt.imshow(conf_matrix, interpolation='nearest', cmap=plt.get_cmap('Blues'))\n", "plt.title('Confusion Matrix of performance by Decision Tree classifier')\n", "plt.colorbar()\n", "tick_marks = [0, 1] # Assuming binary classification (e.g., 0 for non-spam and 1 for spam)\n", "plt.xticks(tick_marks, ['Predicted Ham(Non-spam)', 'Predicted Spam'], rotation=45)\n", "plt.yticks(tick_marks, ['Actual Ham(Non-spam)', 'Actual Spam'])\n", "plt.tight_layout()\n", "for i in range(2):\n", " for j in range(2):\n", " plt.text(j, i, format(conf_matrix[i, j], 'd'), ha=\"center\", va=\"center\", color=\"white\" if conf_matrix[i, j] > conf_matrix.max() / 2. else \"black\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 40, "id": "5c99eda1", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "precision, recall, _ = precision_recall_curve(y_test, y_pred_3)\n", "average_precision = average_precision_score(y_test, y_pred_3)\n", "plt.figure()\n", "plt.step(recall, precision, color='b', where='post')\n", "plt.fill_between(recall, precision, alpha=0.2, color='r')\n", "plt.xlabel('Recall')\n", "plt.ylabel('Precision')\n", "plt.ylim([0.0, 1.05])\n", "plt.xlim([0.0, 1.0])\n", "plt.title(f'Precision-Recall curve of performance by Decision Tree classifier (Average-precision = {average_precision:.2f})')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "88c797ac", "metadata": {}, "source": [ "### [D] Random Forest Classifier" ] }, { "cell_type": "code", "execution_count": 41, "id": "c85e30bc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "RandomForestClassifier()" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "classifier_4 = RandomForestClassifier()\n", "classifier_4.fit(x_train_new, y_train)" ] }, { "cell_type": "code", "execution_count": 42, "id": "5c093900", "metadata": {}, "outputs": [], "source": [ "y_pred_4 = classifier_4.predict(x_test_new)" ] }, { "cell_type": "code", "execution_count": 43, "id": "728ba7bb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Confusion Matrix:\n", "[[1428 2]\n", " [ 44 198]]\n" ] } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_4)\n", "print(\"Confusion Matrix:\")\n", "print(conf_matrix)" ] }, { "cell_type": "code", "execution_count": 44, "id": "c3352829", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.972488038277512\n" ] } ], "source": [ "accuracy_4 = accuracy_score(y_test, y_pred_4)\n", "print(\"Accuracy:\", accuracy_4)" ] }, { "cell_type": "code", "execution_count": 45, "id": "47690de9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Classification Report:\n", " precision recall f1-score support\n", "\n", " 0 0.97 1.00 0.98 1430\n", " 1 0.99 0.82 0.90 242\n", "\n", " accuracy 0.97 1672\n", " macro avg 0.98 0.91 0.94 1672\n", "weighted avg 0.97 0.97 0.97 1672\n", "\n" ] } ], "source": [ "class_report = classification_report(y_test, y_pred_4)\n", "print(\"Classification Report:\")\n", "print(class_report)" ] }, { "cell_type": "code", "execution_count": 46, "id": "d3906d0c", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_4)\n", "plt.figure(figsize=(8, 6))\n", "plt.imshow(conf_matrix, interpolation='nearest', cmap=plt.get_cmap('Blues'))\n", "plt.title('Confusion Matrix of performance by Random Forest classifier')\n", "plt.colorbar()\n", "tick_marks = [0, 1] # Assuming binary classification (e.g., 0 for non-spam and 1 for spam)\n", "plt.xticks(tick_marks, ['Predicted Ham(Non-spam)', 'Predicted Spam'], rotation=45)\n", "plt.yticks(tick_marks, ['Actual Ham(Non-spam)', 'Actual Spam'])\n", "plt.tight_layout()\n", "for i in range(2):\n", " for j in range(2):\n", " plt.text(j, i, format(conf_matrix[i, j], 'd'), ha=\"center\", va=\"center\", color=\"white\" if conf_matrix[i, j] > conf_matrix.max() / 2. else \"black\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 47, "id": "76d885b2", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "precision, recall, _ = precision_recall_curve(y_test, y_pred_4)\n", "average_precision = average_precision_score(y_test, y_pred_4)\n", "plt.figure()\n", "plt.step(recall, precision, color='b', where='post')\n", "plt.fill_between(recall, precision, alpha=0.2, color='r')\n", "plt.xlabel('Recall')\n", "plt.ylabel('Precision')\n", "plt.ylim([0.0, 1.05])\n", "plt.xlim([0.0, 1.0])\n", "plt.title(f'Precision-Recall curve of performance by Random Forest classifier (Average-precision = {average_precision:.2f})')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "26cf1a80", "metadata": {}, "source": [ "### [E] Support Vector Machine Classifier" ] }, { "cell_type": "code", "execution_count": 48, "id": "da7ba132", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SVC()" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "svm = SVC()\n", "classifier_5 = svm\n", "classifier_5.fit(x_train_new, y_train)" ] }, { "cell_type": "code", "execution_count": 49, "id": "70dc549a", "metadata": {}, "outputs": [], "source": [ "y_pred_5 = classifier_5.predict(x_test_new)" ] }, { "cell_type": "code", "execution_count": 50, "id": "26e7732d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.9742822966507177\n" ] } ], "source": [ "accuracy_5 = accuracy_score(y_test, y_pred_5)\n", "print(\"Accuracy:\", accuracy_5)" ] }, { "cell_type": "code", "execution_count": 51, "id": "cb47a595", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Confusion Matrix:\n", "[[1429 1]\n", " [ 42 200]]\n" ] } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_5)\n", "print(\"Confusion Matrix:\")\n", "print(conf_matrix)" ] }, { "cell_type": "code", "execution_count": 52, "id": "eab4b722", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Classification Report:\n", " precision recall f1-score support\n", "\n", " 0 0.97 1.00 0.99 1430\n", " 1 1.00 0.83 0.90 242\n", "\n", " accuracy 0.97 1672\n", " macro avg 0.98 0.91 0.94 1672\n", "weighted avg 0.97 0.97 0.97 1672\n", "\n" ] } ], "source": [ "class_report = classification_report(y_test, y_pred_5)\n", "print(\"Classification Report:\")\n", "print(class_report)" ] }, { "cell_type": "code", "execution_count": 53, "id": "74a2a9b0", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "conf_matrix = confusion_matrix(y_test, y_pred_5)\n", "plt.figure(figsize=(8, 6))\n", "plt.imshow(conf_matrix, interpolation='nearest', cmap=plt.get_cmap('Blues'))\n", "plt.title('Confusion Matrix of performance by Support Vector Machine classifier')\n", "plt.colorbar()\n", "tick_marks = [0, 1] # Assuming binary classification (e.g., 0 for non-spam and 1 for spam)\n", "plt.xticks(tick_marks, ['Predicted Ham(Non-spam)', 'Predicted Spam'], rotation=45)\n", "plt.yticks(tick_marks, ['Actual Ham(Non-spam)', 'Actual Spam'])\n", "plt.tight_layout()\n", "for i in range(2):\n", " for j in range(2):\n", " plt.text(j, i, format(conf_matrix[i, j], 'd'), ha=\"center\", va=\"center\", color=\"white\" if conf_matrix[i, j] > conf_matrix.max() / 2. else \"black\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 54, "id": "a54164eb", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "precision, recall, _ = precision_recall_curve(y_test, y_pred_5)\n", "average_precision = average_precision_score(y_test, y_pred_5)\n", "plt.figure()\n", "plt.step(recall, precision, color='b', where='post')\n", "plt.fill_between(recall, precision, alpha=0.2, color='r')\n", "plt.xlabel('Recall')\n", "plt.ylabel('Precision')\n", "plt.ylim([0.0, 1.05])\n", "plt.xlim([0.0, 1.0])\n", "plt.title(f'Precision-Recall curve of performance by Support Vector Machine classifier (Average-precision = {average_precision:.2f})')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "ed9b82d7", "metadata": {}, "source": [ "#### Individual Accuracy scores of each model" ] }, { "cell_type": "code", "execution_count": 55, "id": "ade78c74", "metadata": {}, "outputs": [], "source": [ "model_accuracies = {\n", " \"MultiNominal Naive Bayes Classifier\": accuracy_1,\n", " \"Logistic Regression Classifer\": accuracy_2,\n", " \"Decision Tree Classifier\": accuracy_3,\n", " \"Random Forest Classfier\": accuracy_4,\n", " \"Support Vector Machine Classifier\": accuracy_5\n", "}" ] }, { "cell_type": "code", "execution_count": 56, "id": "91702b07", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1. MultiNominal Naive Bayes Classifier : 0.9856459330143541\n", "2. Logistic Regression Classifer : 0.9802631578947368\n", "3. Decision Tree Classifier : 0.965311004784689\n", "4. Random Forest Classfier : 0.972488038277512\n", "5. Support Vector Machine Classifier : 0.9742822966507177\n" ] } ], "source": [ "print(\"1. MultiNominal Naive Bayes Classifier : \", accuracy_1)\n", "print(\"2. Logistic Regression Classifer : \", accuracy_2)\n", "print(\"3. Decision Tree Classifier : \", accuracy_3)\n", "print(\"4. Random Forest Classfier : \", accuracy_4)\n", "print(\"5. Support Vector Machine Classifier : \", accuracy_5)" ] }, { "cell_type": "code", "execution_count": 57, "id": "ebbd08e5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Performance Model is MultiNominal Naive Bayes Classifier with an accuracy score of 0.9856459330143541\n" ] } ], "source": [ "best_model_name = max(model_accuracies, key=model_accuracies.get)\n", "best_accuracy = model_accuracies[best_model_name]\n", "\n", "print(f\"Best Performance Model is {best_model_name} with an accuracy score of {best_accuracy}\")" ] }, { "cell_type": "markdown", "id": "168c3269", "metadata": {}, "source": [ "### 6. Saving the best performing Model" ] }, { "cell_type": "code", "execution_count": 58, "id": "bc9e75d9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['multinomial_nb_model.joblib']" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "joblib.dump(classifier_1, 'multinomial_nb_model.joblib')" ] }, { "cell_type": "markdown", "id": "bd7f610c", "metadata": {}, "source": [ "### 7. Evaluating the model performance" ] }, { "cell_type": "code", "execution_count": 59, "id": "adaedd91", "metadata": {}, "outputs": [], "source": [ "def model_eval():\n", " loaded_model = joblib.load('multinomial_nb_model.joblib')\n", " \n", "\n", "\n", " def classify_message(input_message):\n", " \n", " input_message = re.sub(r'[^a-zA-Z0-9\\s]', '', input_message) # Remove special characters\n", " input_message = input_message.lower() # Convert to lowercase\n", " input_message = [input_message] \n", " \n", " input_message_vectorized = cv.transform(input_message)\n", " \n", " \n", " prediction = loaded_model.predict(input_message_vectorized)\n", " \n", " return prediction[0] \n", " # User input\n", " user_input = input(\"Enter a message: \")\n", " \n", " # Call the classify_message function to detect spam or non-spam\n", " result = classify_message(user_input)\n", " \n", " # Display the result to the user\n", " if result == 1:\n", " print(\"Spam detected.\")\n", " else:\n", " print(\"The above entered message is a Non-spam (ham) message.\")" ] }, { "cell_type": "code", "execution_count": 60, "id": "e601d15d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter a message: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\n", "The above entered message is a Non-spam (ham) message.\n" ] } ], "source": [ "model_eval()" ] }, { "cell_type": "code", "execution_count": 61, "id": "4d14eff0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter a message: XXXMobileMovieClub: To use your credit, click the WAP link in the next txt message or click here>> http://wap. xxxmobilemovieclub.com?n=QJKGIGHJJGCBL\n", "Spam detected.\n" ] } ], "source": [ "model_eval()" ] }, { "cell_type": "code", "execution_count": 64, "id": "3690276a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter a message: Dear ADVAIT CHAVAN, ⚡ Offer Ends Tonight! Get CAT 2023 Mock Series for just ₹ 999. Grab now: https://cracku.in/group-offer/catmocks 📣 Results speak for themselves\n", "The above entered message is a Non-spam (ham) message.\n" ] } ], "source": [ "model_eval()" ] }, { "cell_type": "code", "execution_count": 67, "id": "0aa248a4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter a message: Hi Advait, Shhhh. There’s a secret we want to share with you. We know who is going to win the Cricket World Cup. And the answer will leave you amazed ‘cause YOU’re going to be the winner! 🤩 Wondering how? 🤔 By taking part in the World’s Biggest Cricket Quiz Festival, you get a chance to bag rewards that are as exciting as Dhoni’s winning six from 2011: Win cash rewards from a prize pool INR 4 Lakhs 💰 - The overall Grand Finale winner wins a whopping INR 1,00,000/- - Runner up bags INR 50,000/- - Second Runner up bags INR 30,000/- - All 3 remaining finalists win INR 5,000 /- each Exclusive discounts on Unstop Pro 💯 Subscriptions to OTT Play* for Quizzer of the Day 🤩 Amazon vouchers for the rest of the leaderboard worth thousands & much more! *T&C apply\n", "Spam detected.\n" ] } ], "source": [ "model_eval()" ] }, { "cell_type": "code", "execution_count": null, "id": "cc7cf98a", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.13" } }, "nbformat": 4, "nbformat_minor": 5 }