title: scikit learn logistic regression equation
body: <p>I have run the logistic regression on iris dataset. i am clear till this code. after this i want to form the equation to score the test data how to do that? i know i can use predict function to score the test however i want to see the parameters and respective weights. could you please help.  </p>
  
  <pre><code>from sklearn import datasets
  from sklearn.preprocessing import StandardScaler
  from sklearn.linear_model import LogisticRegression
  
  iris = datasets.load_iris()
  
  X = iris.data
  y = iris.target
  
  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3, random_state = 0)
  
  sc = StandardScaler()
  sc.fit(X_train)
  X_train_std = sc.transform(X_train)
  
  lr = LogisticRegression(C = 1000, random_state=0)
  lr.fit(X_train_std, y_train)
  print(lr.coef_)
  print(lr.intercept_)
  </code></pre>
  
  <p>Thanks</p>