main.py

@@ -1,24 +0,0 @@
-import numpy
-import pandas
-import sys
-from sklearn.linear_model import LinearRegression
-
-def trainModel(filePath):
-    trainFrame = pandas.read_csv(filePath, sep='\t', names=['price','mileage','year','brand','engineType','engineCapacity'])
-    dataY = trainFrame[['price']]
-    dataX = trainFrame[['year','mileage','engineCapacity']]
-    model = LinearRegression()
-    model.fit(dataX, dataY)
-    return model
-
-def predictModel(model, filePathIn, filePathOut):
-    inFrame = pandas.read_csv(filePathIn, sep='\t', names=['mileage','year','brand','engineType','engineCapacity'])
-    data = inFrame[['year','mileage','engineCapacity']]
-    prediction = model.predict(data)
-    numpy.savetxt(filePathOut, prediction, fmt='%d', delimiter='\n')
-
-model = trainModel("train/train.tsv")
-predictModel(model, "dev-0/in.tsv", "dev-0/out.tsv")
-predictModel(model, "test-A/in.tsv", "test-A/out.tsv")
-
-