33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
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# Name:fang xiaoyu
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# Time: 2023/3/11 22:05
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.neighbors import KNeighborsClassifier
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from sklearn.metrics import accuracy_score
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from sklearn.metrics import classification_report
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data = pd.read_csv('sufshark_openvpn_tcp+youdao_header.csv')
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data["class1"] = data["class1"].replace({"VPN": 1, "Non-VPN": 0})
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#print(data)
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X_train, X_test, y_train, y_test = train_test_split(
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data.iloc[:, :-1], data.iloc[:, -1], test_size=0.2, random_state=42)
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knn = KNeighborsClassifier(n_neighbors=3)
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knn.fit(X_train, y_train)
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y_pred = knn.predict(X_test)
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accuracy = accuracy_score(y_test, y_pred)
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print(f"Accuracy: {accuracy}")
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print(classification_report(y_test, y_pred))
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#Accuracy: 0.8200959488272921
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# precision recall f1-score support
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#
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# 0 0.79 0.83 0.81 1767
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# 1 0.84 0.81 0.83 1985
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#
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# accuracy 0.82 3752
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# macro avg 0.82 0.82 0.82 3752
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# weighted avg 0.82 0.82 0.82 3752
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