title: Calibrating Probabilities in lightgbm or XGBoost
body: <p>Hi i need help in calibrating probabilities in lightgbm</p>
  
  <p>below is my code</p>
  
  <p>cv_results = lgb.cv(params, 
                      lgtrain, 
                      nfold=10,
                      stratified=False ,
                      num_boost_round = num_rounds,
                      verbose_eval=10,
                      early_stopping_rounds = 50, 
                      seed = 50)</p>
  
  <p>best_nrounds = cv_results.shape[0] - 1</p>
  
  <p>lgb_clf = lgb.train(params, 
                      lgtrain, 
                      num_boost_round=10000 ,
                      valid_sets=[lgtrain,lgvalid],
                      early_stopping_rounds=50,
                      verbose_eval=10)</p>
  
  <p>ypred = lgb_clf.predict(test, num_iteration=lgb_clf.best_iteration)</p>