使用支持向量机算法构建模型

def build_clf(): global data, clf,X_train,X_test,Y_train,Y_test #对用户输入值的合法性判断 if data is None: messagebox.showerror("错误", "请先读取数据！") return

# 创建支持向量机模型
clf = svm.SVC(kernel='linear', C=1)

# 训练模型
clf.fit(X_train, Y_train)
Y_pred = clf.predict(X_test)
accuracy = accuracy_score(Y_test, Y_pred)
precision = precision_score(Y_test, Y_pred, average='macro')
recall = recall_score(Y_test, Y_pred, average='macro')
f1 = f1_score(Y_test, Y_pred, average='macro')
messagebox.showinfo('提示', f'模型构建成功！\n模型预测准确率：{accuracy:.2f}\n模型精确度：{precision:.2f}\n模型召回率：{recall:.2f}\n模型F1值：{f1:.2f}'