sklearn first code 学习笔记

亲测,很准

from sklearn import svm, datasets

class Dataset:
    def __init__(self, name):
        self.name = name

    #下载数据集
    def download_data(self):
        if self.name == 'iris':
            self.downloaded_data = datasets.load_iris()
        elif self.name == 'digits':
            self.downloaded_data = datasets.load_digits()
        else:
            print('Dataset error: no named datasets')

    # 获取数据集data 及 target
    def generate_xy(self):
        self.download_data()
        x = self.downloaded_data.data
        y = self.downloaded_data.target
        print('\nOrginal data looks like this: \n', x)
        print('\nLabels looks like this: \n', y)
        return x,y

    # 分割训练及测试数据集
    def get_train_test_set(self, ratio):
        x, y = self.generate_xy()

        n_samples = len(x)
        n_train = (int)(n_samples * ratio)

        x_train = x[:n_train]
        y_train = y[:n_train]
        x_test = x[n_train:]
        y_test = y[n_train:]
        return x_train, y_train, x_test, y_test

data = Dataset('digits')
x_train, y_train, x_test, y_test = data.get_train_test_set(0.7)

print('*****')
print(x_test[12])
print(y_test[12])
print('*****')

clf = svm.SVC()
clf.fit(x_train, y_train)

test_point = x_test[12]
y_true = y_test[12]

print(clf.predict(test_point))