update

config.txt

@@ -1 +1 @@
---metric RMSE --precision 1
+--precision 1

program-dev0.py

@@ -0,0 +1,24 @@
+import numpy as np
+from sklearn import preprocessing
+from sklearn.pipeline import make_pipeline
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.linear_model import LinearRegression
+from sklearn import linear_model
+import pandas as pd
+
+
+train=pd.read_csv('train/train.tsv',sep='\t',names=['price','mileage','year','brand','engineType','engineCapacity'])
+df = pd.DataFrame(train,columns=['price','mileage','year','brand','engineType','engineCapacity'])
+Y=df[['price']]
+X=df[['year','mileage','engineCapacity']]
+reg = linear_model.LinearRegression()
+reg.fit(X, Y)
+inn=pd.read_csv('dev-0/in.tsv',sep='\t',names=['mileage','year','brand','engineType','engineCapacity'])
+df = pd.DataFrame(inn,columns=['mileage','year','brand','engineType','engineCapacity'])
+r=df[['year','mileage','engineCapacity']]
+y_pred=reg.predict(r)
+y_pred=np.concatenate(y_pred)
+t=np.array2string(y_pred, precision=5, separator='\n',suppress_small=True)
+t=t.lstrip('[').rstrip(']')
+f = open("dev-0/out.tsv", "a")
+f.write(t)

program-testA.py

@@ -0,0 +1,24 @@
+import numpy as np
+from sklearn import preprocessing
+from sklearn.pipeline import make_pipeline
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.linear_model import LinearRegression
+from sklearn import linear_model
+import pandas as pd
+
+
+train=pd.read_csv('train/train.tsv',sep='\t',names=['price','mileage','year','brand','engineType','engineCapacity'])
+df = pd.DataFrame(train,columns=['price','mileage','year','brand','engineType','engineCapacity'])
+Y=df[['price']]
+X=df[['year','mileage','engineCapacity']]
+reg = linear_model.LinearRegression()
+reg.fit(X, Y)
+inn=pd.read_csv('test-A/in.tsv',sep='\t',names=['mileage','year','brand','engineType','engineCapacity'])
+df = pd.DataFrame(inn,columns=['mileage','year','brand','engineType','engineCapacity'])
+r=df[['year','mileage','engineCapacity']]
+y_pred=reg.predict(r)
+y_pred=np.concatenate(y_pred)
+t=np.array2string(y_pred, precision=5, separator='\n',suppress_small=True)
+t=t.lstrip('[').rstrip(']')
+f = open("test-A/out.tsv", "a")
+f.write(t)