ML之LoR&SGD：基于LoR(逻辑回归)、SGD梯度下降算法对乳腺癌肿瘤(10+1)进行二分类预测(良/恶性)
目录
输出结果
设计思路
核心代码
输出结果
breast-cancer size (683, 11)训练集情况 2 3444 168Name: Class, dtype: int64测试集情况 2 100471Name: Class, dtype: int64
设计思路
核心代码
from sklearn.cross_validation import train_test_splitX_train, X_test, y_train, y_test = train_test_split(data[column_names[1:10]], data[column_names[10]], test_size=0.25, random_state=33)ss = StandardScaler()X_train = ss.fit_transform(X_train)X_test = ss.transform(X_test)lr = LogisticRegression()sgdc = SGDClassifier()lr.fit(X_train, y_train)lr_y_predict = lr.predict(X_test) sgdc.fit(X_train, y_train)sgdc_y_predict = sgdc.predict(X_test)lr.score(X_test, y_test))sgdc.score(X_test, y_test))
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