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Add out.tsv

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This commit is contained in:
Iwona Christop 2022-05-19 23:01:39 +02:00
parent de955657c7
commit c183cce711
6 changed files with 46890 additions and 27 deletions
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main.py
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@ -23,27 +23,42 @@ def readInput(dir):
def writeOutput(output, dir): def writeOutput(output, dir):
with open(dir, 'w', newline='') as f: with open(dir, 'w', newline='') as f:
writer = csv.writer(f) writer = csv.writer(f)
writer.writerows(output) for row in output:
writer.writerow([row])
if __name__ == '__main__': if __name__ == '__main__':
train = pd.DataFrame(readInput('train/train.tsv.xz'), print('Reading input...')
train = pd.DataFrame(readInput('train/train.tsv.xz')[:10000],
columns=['Beginning', 'End', 'Title', 'Source', 'X']) columns=['Beginning', 'End', 'Title', 'Source', 'X'])
train['Y'] = train.apply(lambda x: (float(x.Beginning) + float(x.End))/2, axis=1) train['Y'] = train.apply(lambda x: (float(x.Beginning) + float(x.End))/2, axis=1)
train = train.drop(columns=['Beginning', 'End', 'Title', 'Source']) train = train.drop(columns=['Beginning', 'End', 'Title', 'Source'])
estimators = [('tfidf', TfidfVectorizer()), ('linearRegression', LinearRegression())] estimators = [('tfidf', TfidfVectorizer()), ('linearRegression', LinearRegression())]
print('Creating pipeline...')
model = Pipeline(estimators) model = Pipeline(estimators)
print('Fitting model...')
model.fit(train.X, train.Y) model.fit(train.X, train.Y)
print('dev-0...')
# dev-0 # dev-0
testX = readInput('dev-0/in.tsv') testX = readInput('dev-0/in.tsv')
writeOutput(model.predict(testX), 'dev-0/out.tsv') predicted = model.predict(testX)
predicted = [str(x) for x in predicted.tolist()]
writeOutput(predicted, 'dev-0/out.tsv')
print('dev-1...')
# dev-1 # dev-1
testX = readInput('dev-1/in.tsv') testX = readInput('dev-1/in.tsv')
writeOutput(model.predict(testX), 'dev-1/out.tsv') predicted = model.predict(testX)
predicted = [str(x) for x in predicted.tolist()]
writeOutput(predicted, 'dev-1/out.tsv')
print('test-A...')
# test-A # test-A
testX = readInput('test-A/in.tsv') testX = readInput('test-A/in.tsv')
writeOutput(model.predict(testX), 'test-A/out.tsv') predicted = model.predict(testX)
predicted = [str(x) for x in predicted.tolist()]
writeOutput(predicted, 'test-A/out.tsv')

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