random forest classifier predict probability does only 1.0 code example

Example 1: how to improve accuracy of random forest classifier

# Find number of features for cumulative importance of 95%# Add 1 because Python is zero-indexedprint('Number of features for 95% importance:', np.where(cumulative_importances > 0.95)[0][0] + 1)Number of features for 95% importance: 6

Example 2: how to improve accuracy of random forest classifier

def display(results):
    print(f'Best parameters are: {results.best_params_}')
    print("\n")
    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}')