I implemented SelectKBest from sklearn and I want to get the names of the K best col, not just the values of each col.
what do I need to do?
my code:
X_new = SelectKBest(chi2, k=2).fit_transform(X, y)
X_new.shape
X_new is a numpy.ndarray and it has k col but without the col names.
You can get the indices of the selected features.
Example 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))
Now if you really want to get the actual names of the columns we need to use pandas.
Example 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()
Result:
Index([u'petal length (cm)', u'petal width (cm)'], dtype='object')
['petal length (cm)', 'petal width (cm)']
['petal length (cm)', 'petal width (cm)']
model= SelectKBest(f_classif, k=8).fit(X,Y)
Selected_feature_names=X.columns[model.get_support()]
