five modes duplication

Knn_test.py

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