The score we got with the SVC classifier was not that good. So now we will train and predict the dataset using a RandomForest classifier.
Import RandomForestClassifier from sklearn:
from sklearn.ensemble import << your code goes here >>
Train and evaluate the RandomForestClassfier:
forest_clf = << your code goes here >>(n_estimators=100, random_state=42)
forest_scores = cross_val_score(forest_clf, X_train, y_train, cv=10)
forest_scores.mean()
Note - Having trouble with the assessment engine? Follow the steps listed here
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