Grid search has been performed by changing various hyperparameters with the following settings. However, readers are encouraged to try other parameters to explore further in this space.
- Number of trees is (1000,2000,3000)
- Maximum depth is (100,200,300)
- Minimum samples per split are (2,3)
- Minimum samples in leaf node are (1,2)
Import Pipeline as follows:
>>> from sklearn.pipeline import Pipeline>>> from sklearn.model_selection import train_test_split,GridSearchCV
The Pipeline function creates the combinations which will be applied one by one sequentially to determine the best possible combination:
>>> pipeline = Pipeline([ ('clf',RandomForestClassifier(criterion='gini'))])>>> parameters = { ... 'clf__n_estimators':(1000,2000,3000), ...
