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how to improve accuracy of random forest classifier

from sklearn.model_selection import GridSearchCV
cv = GridSearchCV(rfc,parameters,cv=5)
cv.fit(train_features,train_label.values.ravel())

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how to improve accuracy of random forest classifier

def display(results):
    print(f'Best parameters are: {results.best_params_}')
    print("
")
    mean_score = results.cv_results_['mean_test_score']
    std_score = results.cv_results_['std_test_score']
    params = results.cv_results_['params']
    for mean,std,params in zip(mean_score,std_score,params):
        print(f'{round(mean,3)} + or -{round(std,3)} for the {params}')

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how to improve accuracy of random forest classifier

display(cv)

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how to improve accuracy of random forest classifier

how to improve accuracy of random forest classifier

how to improve accuracy of random forest classifier

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