42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
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import inout as io
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categories = {'news': 0, 'sport': 1, 'opinion': 2,
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'business': 3, 'culture': 4, 'lifestyle': 5, 'removed': 6}
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def trainingData(data, target):
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data = io.read(data)
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years = [x[0] for x in data]
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text = [x[2].replace('\n', '').replace(':', '') for x in data]
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target = [categories[x[0].replace('\n', '')] for x in io.read(target)]
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data = []
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for i in range(len(text)):
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data.append(' |Text ' + text[i] + ' |Year ' + years[i])
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return {'data': data, 'target': target}
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def predictFuture(test):
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data = io.read(test + '/in.tsv')
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years = [x[0] for x in data]
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text = [x[2].replace('\n', '').replace(':', '') for x in data]
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data = []
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for i in range(len(text)):
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data.append(' |Text ' + text[i] + ' |Year ' + years[i])
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with open(test + '/vw-in', 'w', encoding='utf-8') as f:
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for text in data:
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f.write('1' + text + '\n')
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if __name__ == '__main__':
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ireland_news_train = trainingData('train/in.tsv.xz', 'train/expected.tsv.xz')
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with open('train/vw-in', 'w', encoding='utf-8') as f:
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for target, text in zip(ireland_news_train['target'], ireland_news_train['data']):
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f.write(str(target + 1) + text + '\n')
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predictFuture('dev-0')
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predictFuture('test-A')
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predictFuture('test-B')
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