forked from kubapok/auta-public
25 lines
888 B
Python
25 lines
888 B
Python
import numpy
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import pandas
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import sys
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from sklearn.linear_model import LinearRegression
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def trainModel(filePath):
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trainFrame = pandas.read_csv(filePath, sep='\t', names=['price','mileage','year','brand','engineType','engineCapacity'])
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dataY = trainFrame[['price']]
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dataX = trainFrame[['year','mileage','engineCapacity']]
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model = LinearRegression()
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model.fit(dataX, dataY)
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return model
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def predictModel(model, filePathIn, filePathOut):
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inFrame = pandas.read_csv(filePathIn, sep='\t', names=['mileage','year','brand','engineType','engineCapacity'])
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data = inFrame[['year','mileage','engineCapacity']]
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prediction = model.predict(data)
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numpy.savetxt(filePathOut, prediction, fmt='%d', delimiter='\n')
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model = trainModel("train/train.tsv")
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predictModel(model, "dev-0/in.tsv", "dev-0/out.tsv")
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predictModel(model, "test-A/in.tsv", "test-A/out.tsv")
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