sklearn example params

## Random Forest params
rf_param_grid = {"max_depth": [None],
              "max_features": [1, 3],
              "min_samples_split": [2, 3],
              "min_samples_leaf": [1, 3],
              "bootstrap": [False],
              "n_estimators" :[100],
              "criterion": ["gini"]}

## Extra Trees params
ex_param_grid = {"max_depth": [None],
              "max_features": [1, 3],
              "min_samples_split": [2, 3],
              "min_samples_leaf": [1, 3],
              "bootstrap": [False],
              "n_estimators" :[100],
              "criterion": ["gini"]}
     
# Gradient Boosting params
gb_param_grid = {'loss' : ["deviance"],
              'n_estimators' : [100,200],
              'learning_rate': [0.1, 0.05],
              'max_depth': [4, 8],
              'min_samples_leaf': [100],
              'max_features': [0.3] 
              }
# SVC params
svc_param_grid = {'kernel': ['rbf'], 
                  'gamma': [ 0.001, 0.01, 0.1, 1],
                  'C': [1, 10, 50, 100,200,300, 1000]}
             
# AdaBoost params
ada_param_grid = {"base_estimator__criterion" : ["gini", "entropy"],
              "base_estimator__splitter" :   ["best", "random"],
              "algorithm" : ["SAMME","SAMME.R"],
              "n_estimators" :[1,2],
              "learning_rate":  [0.0001, 0.001, 0.01, 0.1, 0.2, 0.3,1.5]}