本文整理汇总了Python中sklearn.feature_selection.SelectFpr.fit_transform方法的典型用法代码示例。如果您正苦于以下问题：Python SelectFpr.fit_transform方法的具体用法？Python SelectFpr.fit_transform怎么用？Python SelectFpr.fit_transform使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.feature_selection.SelectFpr的用法示例。
在下文中一共展示了SelectFpr.fit_transform方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: select_with_fpr
# 需要导入模块: from sklearn.feature_selection import SelectFpr [as 别名]
# 或者: from sklearn.feature_selection.SelectFpr import fit_transform [as 别名]
def select_with_fpr(train, test):
train_data = train.drop('ID', axis=1)
test_data = test.drop('ID', axis=1)
train_y = train_data['TARGET']
train_X = train_data.drop('TARGET', 1)
fpr = SelectFpr(alpha = 0.001)
features = fpr.fit_transform(train_X, train_y)
print('Fpr выбрал {} признаков.'.format(features.shape[1]))
col_numbers = fpr.get_support()
columns = np.delete(train_data.columns.values, train_data.shape[1] - 1, axis=0)
features = []
i = 0
for i in range(len(columns)):
if col_numbers[i] == True:
features.append(columns[i])
new_train = train[['ID'] + features + ['TARGET']]
new_train.to_csv('train_after_fpr.csv')
new_test = test[['ID'] + features]
new_test.to_csv('test_after_fpr.csv')