diff --git a/hpo - 副本.PY b/hpo - 副本.PY
deleted file mode 100644
index 9130867..0000000
--- a/hpo - 副本.PY	
+++ /dev/null
@@ -1,31 +0,0 @@
-from sklearn.datasets import load_iris
-from sklearn.model_selection import train_test_split
-from sklearn.svm import SVC
-import argparse
-
-# 加载数据集
-iris = load_iris()
-X = iris.data
-y = iris.target
-
-# 划分数据集
-X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
-
-# 参数解析
-parser = argparse.ArgumentParser(description='SVM Model for Iris dataset')
-parser.add_argument('--C', type=float, default=1.0, help='Regularization parameter')
-parser.add_argument('--kernel', type=str, default='rbf', help='Kernel type')
-parser.add_argument('--gamma', type=float, default='scale', help='Kernel coefficient')
-
-args = parser.parse_args()
-
-# 定义支持向量机模型并设置参数
-svm = SVC(C=args.C, kernel=args.kernel, gamma=args.gamma)
-
-# 在训练集上拟合模型
-svm.fit(X_train, y_train)
-
-# 输出模型在测试集上的准确率
-test_accuracy = svm.score(X_test, y_test)
-print(f"Accuracy={test_accuracy}")
-