Add a problem solution

This problem "Day 6: Multiple Linear Regression: Predicting
 House Prices" comes from Intro to Statistics contest.

Author: Derek Hao Hu

predicting-house-prices.py

@@ -0,0 +1,32 @@
+#predicting-house-prices.py
+#Day 6: Multiple Linear Regression: Predicting House Prices
+#Intro to Statistics
+#By derekhh
+#Apr 2, 2016
+
+from sklearn import linear_model
+
+f, n = input().split()
+f = int(f)
+n = int(n)
+
+clf = linear_model.LinearRegression()
+x_train = []
+y_train = []
+
+for i in range(n):
+    tmp = [float(n) for n in input().split()]
+    x_train.append(tmp[0: len(tmp) - 1])
+    y_train.append(tmp[len(tmp) - 1])
+
+clf.fit(x_train, y_train)
+
+x_test = []
+n = int(input())
+for i in range(n):
+    tmp = [float(n) for n in input().split()]
+    x_test.append(tmp)
+
+y_test = clf.predict(x_test)
+for y in y_test:
+    print(y)