我从sklearn实现了SelectKBest,我希望得到K最佳col的名称,而不仅仅是每个col的值。
我需要做什么?
我的代码:
X_new = SelectKBest(chi2, k=2).fit_transform(X, y)
X_new.shape
X_new是一个numpy.ndarray,它有k col但没有col名称。
答案 0 :(得分:7)
您可以获取所选功能的索引。
示例1 :
from sklearn.datasets import load_iris
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import chi2
iris = load_iris()
X, y = iris.data, iris.target
selector = SelectKBest(chi2, k=2)
selector.fit(X, y)
X_new = selector.transform(X)
X_new.shape
print(selector.get_support(indices=True))
现在,如果您真的想获得列的实际名称,我们需要使用pandas 。
示例2 :
from sklearn.datasets import load_iris
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import chi2
import pandas as pd
iris = load_iris()
X = pd.DataFrame(iris.data, columns=iris.feature_names)
y = pd.DataFrame(iris.target)
selector = SelectKBest(chi2, k=2)
selector.fit(X, y)
X_new = selector.transform(X)
print(X_new.shape)
X.columns[selector.get_support(indices=True)]
# 1st way to get the list
vector_names = list(X.columns[selector.get_support(indices=True)])
print(vector_names)
#2nd way
X.columns[selector.get_support(indices=True)].tolist()
结果:
Index([u'petal length (cm)', u'petal width (cm)'], dtype='object')
['petal length (cm)', 'petal width (cm)']
['petal length (cm)', 'petal width (cm)']
答案 1 :(得分:3)
model = SelectKBest(f_classif,k = 8).fit(X,Y)
<强> Selected_feature_names = X.columns [model.get_support()] 强>
答案 2 :(得分:2)
model=SelectKBest(k=5)
model.fit(X,y)
print(model.get_params)