lin reg

main.py

@@ -0,0 +1,24 @@
+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")
+
+