k = 5
fold = 10
dataset = Dataset('', '')
dataset.file_folder_path = '../data/input/'
method = Method('', '')
method.k = k
evaluation = Evaluation('')
result = Result('', '')
result.k = k
setting = Setting('', '', dataset, method, result, evaluation)
setting.fold = fold
setting.load_classify_save()
if 1:
fold = 10
k = 5
result = Result('', '')
result.k = k
evaluation = Evaluation('')
evaluation_result_of_each_fold = []
for fold_count in range(1, fold + 1):
final_result = result.load(fold_count)
predict_result = final_result['predict_result']
ground_truth = final_result['ground_truth']
evaluation_result_of_each_fold.append(evaluation.evaluate(predict_result, ground_truth))
