1.13.1. Removing features with low variance 

移除方差较小的feature

from sklearn.feature_selection import VarianceThreshold
X = [[0, 0, 1], [0, 1, 0], [1, 0, 0], [0, 1, 1], [0, 1, 0], [0, 1, 1]]
sel = VarianceThreshold(threshold=(.8 * (1 - .8)))
sel.fit_transform(X)

 

1.13.2. Univariate feature selection

 变量特征选择 

 

1.13.3. Recursive feature elimination

递归特征剔除

1.13.4. Feature selection using SelectFromModel

使用 SelectFromModel进行筛选

1.13.4.1. L1-based feature selection 基于L1正则的特征选择

1.13.4.2. Tree-based feature selection  基于树的特征选择

 

1.13.5. Feature selection as part of a pipeline

使用管道流程控制进行特征选择 

clf = Pipeline([
  ('feature_selection', SelectFromModel(LinearSVC(penalty="l1"))),
  ('classification', RandomForestClassifier())
])
clf.fit(X, y)

 

https://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection