grityu-model-duplication/Knn_test.py

# 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

#读取数据
data = pd.read_csv('sufshark_openvpn_tcp+youdao_header.csv')

#将类别标签转换为数字
data["class1"] = data["class1"].replace({"VPN": 1, "Non-VPN": 0})

#print(data)

#划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(
    data.iloc[:, :-1], data.iloc[:, -1], test_size=0.2, random_state=42)

#创建KNN分类器
knn = KNeighborsClassifier(n_neighbors=3)

#训练模型
knn.fit(X_train, y_train)

#在测试集上测试模型性能
y_pred = knn.predict(X_test)
# accuracy = accuracy_score(y_test, y_pred)
# print(f"Accuracy: {accuracy}")

#输出测试结果
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