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"""ML.ipynb |
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Automatically generated by Colab. |
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Original file is located at |
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https://colab.research.google.com/drive/1N6R2R3PY04PitBN4M6QNX-tuBPdqglVz |
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""" |
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from google.colab import drive |
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drive.mount('/content/drive') |
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import pandas as pd |
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file_path = '/content/drive/My Drive/CIS 519 Final Project/Dataset/cleaned_headlines.csv' |
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df = pd.read_csv(file_path) |
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df |
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class_counts = df['outlet'].value_counts() |
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print(class_counts) |
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from sklearn.model_selection import train_test_split |
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X = df['title'] |
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y = df['labels'] |
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) |
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from sklearn.feature_extraction.text import TfidfVectorizer |
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tfidf = TfidfVectorizer(max_features=5000, ngram_range=(1, 2), stop_words='english') |
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X_train_tfidf = tfidf.fit_transform(X_train) |
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X_test_tfidf = tfidf.transform(X_test) |
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"""# Logistic Regression""" |
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from sklearn.linear_model import LogisticRegression |
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from sklearn.metrics import accuracy_score, classification_report |
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model = LogisticRegression(max_iter=200) |
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model.fit(X_train_tfidf, y_train) |
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y_pred = model.predict(X_test_tfidf) |
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accuracy = accuracy_score(y_test, y_pred) |
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print(f"Logistic Regression Accuracy: {accuracy:.4f}") |
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print(classification_report(y_test, y_pred)) |
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"""# Random Forest""" |
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from sklearn.ensemble import RandomForestClassifier |
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model = RandomForestClassifier(n_estimators=100, random_state=42) |
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model.fit(X_train_tfidf, y_train) |
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y_pred = model.predict(X_test_tfidf) |
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accuracy = accuracy_score(y_test, y_pred) |
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print(f"Random Forest Accuracy: {accuracy:.4f}") |
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print(classification_report(y_test, y_pred)) |
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"""# Support Vector Machine""" |
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from sklearn.svm import SVC |
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svm_model = SVC(kernel='linear', random_state=42) |
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svm_model.fit(X_train_tfidf, y_train) |
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y_pred = svm_model.predict(X_test_tfidf) |
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accuracy = accuracy_score(y_test, y_pred) |
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print(f"Random Forest Accuracy: {accuracy:.4f}") |
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print(classification_report(y_test, y_pred)) |
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