title: How to find the features names of the coefficients using StackingClassifier + Logistic Regression (binary classification)
body: <p>I am trying to use StackingClassifier with Logistic regression (Binary Classifier).
  Sample code:</p>
  
  <pre><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
  </code></pre>
  
  <p>For each classifier, Initial logistic regression gives a probability value for two classes. As I am using stacking 5 classifiers, <code>sclf.meta_clf_.coef_</code> gives 10 weights values.</p>
  
  <blockquote>
    <p>array([[-0.96815163,  1.25335525, -0.03120535,  0.8533569 , -2.6250897 ,
             1.98034805, -0.361378  ,  0.00571954, -0.03206343,  0.53138651]])</p>
  </blockquote>
  
  <p>I am confused about the order of weight values. means</p>
  
  <ul>
  <li><p>Are the 1st two values <code>(-0.96815163,  1.25335525)</code> for first logistic regression <code>LR1</code>?</p></li>
  <li><p>Are the 2nd two values <code>(-0.03120535,  0.8533569)</code> for first logistic regression <code>LR2</code>?</p></li>
  </ul>
  
  <p>I want to find out which values are for which Logistic Regression (LR) for the stacking classifier.</p>
  
  <p>Please Help.</p>