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33 lines
1.3 KiB
33 lines
1.3 KiB
from eval.metrics import f1_score
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import utils.constants as const
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from sklearn.metrics import f1_score as f1
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import os
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from utils.csv import read_csv_file
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y_true = ['positive', 'positive', 'negative', 'negative', 'positive', 'positive', 'negative', 'negative', 'positive', 'positive', 'negative', 'negative', 'positive', 'positive', 'negative', 'negative']
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y_pred = ['positive', 'negative', 'negative', 'positive', 'positive', 'negative', 'negative', 'positive', 'positive', 'negative', 'negative', 'positive', 'positive', 'negative', 'negative', 'negative']
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result_list = f1_score(y_true, y_pred, ['positive', 'negative'], const.AVG_MICRO)
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for result in result_list:
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result.print_result()
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print('SK Learn F1 Score (MICRO):: ', f1(y_true, y_pred, ['positive', 'negative'], average='micro'))
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result_list = f1_score(y_true, y_pred, ['positive', 'negative'], const.AVG_MACRO)
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for result in result_list:
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result.print_result()
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print('SK Learn F1 Score (MACRO):: ', f1(y_true, y_pred, ['positive', 'negative'], average='macro'))
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project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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train_file_path = project_root+'/data/tsv/train.tsv'
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print(train_file_path)
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data = read_csv_file(csv_file_path=train_file_path, delimiter='\t')
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for inst in data[:5]:
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inst.print()
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