title: Hyperparameter Tuning on Logistic Regression
body: <p>I was building a <strong>classification model</strong> on predicting water quality.
  I intend to do <em><strong>Hyper-parameter tuning</strong></em> for the <strong>Logistic Regression</strong> model.
  <strong>Here is the code</strong>..</p>
  <p>params =</p>
  <pre><code>     [{'Penalty':['l1','l2','elasticnet','none'],
         
        'Solver':['liblinear']}]
        
       grid= GridSearchCV(estimator=LogisticRegression(),param_grid=params,cv=10,scoring='f1_macro')
  </code></pre>
  <p><strong>But i am getting this error</strong></p>
  <p>ValueError: Invalid parameter Penalty for estimator LogisticRegression(). Check the list of available parameters with <code>estimator.get_params().keys()</code>.</p>
  <p>~~Any suggestions will be greatly appreciated.. Thank You..</p>