直接贴代码吧：
1 # -*- coding:UTF-8 -*-
2 from sklearn import datasets
3 from sklearn.cross_validation import train_test_split
4 from sklearn import preprocessing
5 from sklearn.linear_model import SGDClassifier
6 from sklearn import metrics
7 iris = datasets.load_iris()
8 X_iris, y_iris = iris.data, iris.target
9 X, y = X_iris[:,:2], y_iris
10 # 将数据分为训练集和测试集
11 X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.25, random_state=33)
12 # 标准化数据
13 scaler = preprocessing.StandardScaler().fit(X_train)
14 X_train = scaler.transform(X_train)
15 X_test = scaler.transform(X_test)
16 # 初始化分类器对象
17 clf = SGDClassifier()
18 clf.fit(X_train,y_train)
19 y_pred = clf.predict(X_test)
20 # 评估分类器的表现
21 print metrics.accuracy_score(y_test,y_pred)
22 print metrics.classification_report(y_test, y_pred, target_names=iris.target_names)
23 # confusion 矩阵
24 print metrics.confusion_matrix(y_test,y_pred)
参考：《learning scikit-learn machine learning in python》