def thresholdsToLatex(path='dfs/2017/1111_workreduced.csv'):
df = pd.read_csv(path, index_col=0)
results = {}
results['WorkReducedLowerBound'] = df.loc[:, 'fnr'].iloc[-1]
results['WorkReducedUpperBound'] = 100 - df.loc[:, 'fpr'].iloc[-1]
results['WorkReducedHundredMinusUpperBound'] = df.loc[:, 'fpr'].iloc[-1]
results['WorkReducedTwoPercent'] = df.loc[:, 'sum'].iloc[-1]
results['WorkReducedHundredMinusTwoPercent'] = 100 - df.loc[:,
'sum'].iloc[-1]
# results['WorkReducedOnePercent'] = df.iloc[2,2]
# results['WorkReducedPointFivePercent'] = df.iloc[1,2]
# results['WorkReducedPointOnePercent'] = df.iloc[0,2]
macroify.append_file(results)
print(
'Accuracy',
accuracy_score(ensemble_labels_priori, ensemble_predictions_priori) *
100)
print('F1',
f1_score(ensemble_labels_priori, ensemble_predictions_priori) * 100)
print(
'Precision',
precision_score(ensemble_labels_priori, ensemble_predictions_priori) *
100)
print(
'Recall',
recall_score(ensemble_labels_priori, ensemble_predictions_priori) *
100)
total_manual = workreduceddict[0.01]['total_manual']
results[strategy + 'WorkReducedOnePercent'] = (
total_amount_of_2018_domains - total_manual -
manual_added_to_trainingset) / total_amount_of_2018_domains * 100
total_manual = workreduceddict[0.005]['total_manual']
results[strategy + 'WorkReducedPointFivePercent'] = (
total_amount_of_2018_domains - total_manual -
manual_added_to_trainingset) / total_amount_of_2018_domains * 100
total_manual = workreduceddict[0.001]['total_manual']
results[strategy + 'WorkReducedPointOnePercent'] = (
total_amount_of_2018_domains - total_manual -
manual_added_to_trainingset) / total_amount_of_2018_domains * 100
macroify.append_file(results)