# 加载库
from sklearn.datasets import load_iris
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection...import make_regression
from sklearn.feature_selection import RFECV
from sklearn import datasets, linear_model...= RFECV(estimator=ols, step=1, scoring='neg_mean_squared_error')
# 拟合递归特征消除器
rfecv.fit(X, y)
# 递归特征消除...的类 1
X = [[0, 1, 0],
[0, 1, 1],
[0, 1, 0],
[0, 1, 1],
[1, 0, 0]]
在二元特征(即伯努利随机变量)中,...()
# 创建特征和目标
X = iris.data
y = iris.target
# 使用方差阈值 0.5 创建 VarianceThreshold 对象
thresholder = VarianceThreshold