def display_results(self):
# Extract scores for plotting
self.cv_mean_scores = [
round(result[1], self.SCORE_DECIMAL_PLACES)
for result in self.results
]
self.test_scores = [
round(result[2], self.SCORE_DECIMAL_PLACES)
for result in self.results
]
self.elapsed_times = [
round(result[3], self.TIME_DECIMAL_PLACES)
for result in self.results
]
create_2_bar_plot(self.classifier_name_shortcut_list,
'Classifier scores',
'Accuracy',
self.cv_mean_scores,
self.test_scores,
'cv means',
'test set',
y_range_tuple=(0, 1),
should_autolabel=True)
create_bar_plot(self.classifier_name_shortcut_list,
'Elapsed training times',
'Time in seconds',
self.elapsed_times,
color='red')
self.print_results_table()
test_scores = [round(result[2], SCORE_DECIMAL_PLACES) for result in results]
elapsed_times = [round(result[3], TIME_DECIMAL_PLACES) for result in results]
# create_bar_plot(classifier_name_shortcut_list, 'Classifier scores', 'Accuracy',
# cv_mean_scores, y_range_tuple=(0, 1))
create_2_bar_plot(classifier_name_shortcut_list,
'Classifier scores',
'Accuracy',
cv_mean_scores,
test_scores,
'cv means',
'test set',
y_range_tuple=(0, 1),
should_autolabel=False)
create_bar_plot(classifier_name_shortcut_list,
'Elapsed training times',
'Time in seconds',
elapsed_times,
color='red')
# results_df = pd.DataFrame(
# [[classifier_name_shortcut_list[i], results[i][1], results[i][2]] for i in
# range(0, len(results))]).T
results_df = pd.DataFrame([[
round(item[1], SCORE_DECIMAL_PLACES),
round(item[2], SCORE_DECIMAL_PLACES)
] for item in results]).T
results_df.columns = classifier_name_shortcut_list
results_df.index = ['CV Mean', 'Test accuracy']
results_df.to_clipboard()