如何使用StackingClassifier + Logistic回归（二进制分类）查找系数的特征名称

Question

I am trying to use StackingClassifier with Logistic regression (Binary Classifier). Sample code:

from sklearn.datasets import load_iris
from mlxtend.classifier import StackingClassifier
from sklearn.linear_model import LogisticRegression


iris = load_iris()
X = iris.data
y = iris.target

y[y == 2] = 1 #Make it binary classifier

LR1 = LogisticRegression(penalty='l1')
LR2 = LogisticRegression(penalty='l1')
LR3 = LogisticRegression(penalty='l1')
LR4 = LogisticRegression(penalty='l1')
LR5 = LogisticRegression(penalty='l1')


clfs1= [LR1, LR2]
clfs2= [LR3, LR4, LR5]

cls_=[]
cls_.append(clfs1)
cls_.append(clfs2)

sclf = StackingClassifier(classifiers=sum(cls_,[]), 
    meta_classifier=LogisticRegression(penalty='l1'), use_probas=True, average_probas=False)

sclf.fit(X, y)

sclf.meta_clf_.coef_ #give the weight values

For each classifier, Initial logistic regression gives a probability value for two classes. As I am using stacking 5 classifiers, sclf.meta_clf_.coef_ gives 10 weights values.

array([[-0.96815163, 1.25335525, -0.03120535, 0.8533569 , -2.6250897 , 1.98034805, -0.361378 , 0.00571954, -0.03206343, 0.53138651]])

I am confused about the order of weight values. means

• Are the 1st two values (-0.96815163, 1.25335525) for first logistic regression LR1 ?

• Are the 2nd two values (-0.03120535, 0.8533569) for first logistic regression LR2 ?

I want to find out which values are for which Logistic Regression (LR) for the stacking classifier.

Please Help.

Answer 1

If your output is:

array([[-0.96815163, 1.25335525, -0.03120535, 0.8533569 , -2.6250897 , 1.98034805, -0.361378 , 0.00571954, -0.03206343, 0.53138651]])

Then,

-0.96815163, 1.25335525: the probability of 0 and 1 for LR1

-0.03120535, 0.8533569: the probability of 0 and 1 for LR2

-2.6250897, 1.98034805: the probability of 0 and 1 for LR3

-0.361378, 0.00571954: the probability of 0 and 1 for LR4

-0.03206343, 0.53138651: the probability of 0 and 1 for LR5