47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
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# Name:fang xiaoyu
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# Time: 2023/3/11 22:28
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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.tree import DecisionTreeClassifier
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from sklearn.metrics import accuracy_score
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from sklearn import preprocessing
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from sklearn import tree
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from sklearn.metrics import classification_report
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# 加载CSV文件
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data = pd.read_csv('sufshark_openvpn_tcp+youdao_header.csv')
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# 将类别转换为数字标签
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# le = preprocessing.LabelEncoder()
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# data['label'] = le.fit_transform(data['label'])
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data["class1"] = data["class1"].replace({"VPN": 1, "Non-VPN": 0})
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# 分离特征和类别
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X = data.iloc[:, :-1]
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y = data.iloc[:, -1]
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# 划分数据集
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
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# 初始化分类器并训练模型
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clf = DecisionTreeClassifier(criterion="entropy")
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clf.fit(X_train, y_train)
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# 预测测试数据集
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y_pred = clf.predict(X_test)
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# 评估分类器的性能
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print("Accuracy:", accuracy_score(y_test, y_pred))
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print(classification_report(y_test, y_pred))
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# 可视化决策树
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tree.plot_tree(clf)
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#Accuracy: 0.8841506751954513
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# precision recall f1-score support
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#
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# 0 0.89 0.86 0.87 2708
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# 1 0.88 0.90 0.89 2920
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#
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# accuracy 0.88 5628
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# macro avg 0.88 0.88 0.88 5628
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# weighted avg 0.88 0.88 0.88 5628
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