Predicting House Price

My boss give me the challenge “how to predict house prices”. I wondered what to do… It’s difficult because i don’t know what is the feature1 and feature2. How to start?

Input Training

Content training.csv file

features1,features2,price
0.44,0.68,511.14
0.99,0.23,717.1
0.84,0.29,607.91
0.28,0.45,270.4
0.07,0.83,289.88
0.66,0.8,830.85
0.73,0.92,1038.09
0.57,0.43,455.19
0.43,0.89,640.17
0.27,0.95,511.06
0.43,0.06,177.03
0.87,0.91,1242.52
0.78,0.69,891.37
0.9,0.94,1339.72
0.41,0.06,169.88
0.52,0.17,276.05
0.47,0.66,517.43
0.65,0.43,522.25
0.85,0.64,932.21
0.93,0.44,851.25
0.41,0.93,640.11
0.36,0.43,308.68
0.78,0.85,1046.05
0.69,0.07,332.4
0.04,0.52,171.85
0.17,0.15,109.55
0.68,0.13,361.97
0.84,0.6,872.21
0.38,0.4,303.7
0.12,0.65,256.38
0.62,0.17,341.2
0.79,0.97,1194.63
0.82,0.04,408.6
0.91,0.53,895.54
0.35,0.85,518.25
0.57,0.69,638.75
0.52,0.22,301.9
0.31,0.15,163.38
0.6,0.02,240.77
0.99,0.91,1449.05
0.48,0.76,609.0
0.3,0.19,174.59
0.58,0.62,593.45
0.65,0.17,355.96
0.6,0.69,671.46
0.95,0.76,1193.7
0.47,0.23,278.88
0.15,0.96,411.4
0.01,0.03,42.08
0.26,0.23,166.19
0.01,0.11,58.62
0.45,0.87,642.45
0.09,0.97,368.14
0.96,0.25,702.78
0.63,0.58,615.74
0.06,0.42,143.79
0.1,0.24,109.0
0.26,0.62,328.28
0.41,0.15,205.16
0.91,0.95,1360.49
0.83,0.64,905.83
0.44,0.64,487.33
0.2,0.4,202.76
0.43,0.12,202.01
0.21,0.22,148.87
0.88,0.4,745.3
0.31,0.87,503.04
0.99,0.99,1563.82
0.23,0.26,165.21
0.79,0.12,438.4
0.02,0.28,98.47
0.89,0.48,819.63
0.02,0.56,174.44
0.92,0.03,483.13
0.72,0.34,534.24
0.3,0.99,572.31
0.86,0.66,957.61
0.47,0.65,518.29
0.79,0.94,1143.49
0.82,0.96,1211.31
0.9,0.42,784.74
0.19,0.62,283.7
0.7,0.57,684.38
0.7,0.61,719.46
0.69,0.0,292.23
0.98,0.3,775.68
0.3,0.08,130.77
0.85,0.49,801.6
0.73,0.01,323.55
1.0,0.23,726.9
0.42,0.94,661.12
0.49,0.98,771.11
0.89,0.68,1016.14
0.22,0.46,237.69
0.34,0.5,325.89
0.99,0.13,636.22
0.28,0.46,272.12
0.87,0.36,696.65
0.23,0.87,434.53
0.77,0.36,593.86

Input Test

0.49 0.18
0.57 0.83
0.56 0.64
0.76 0.18

Output
Predicting house price

105.22
142.68
132.94
129.71

Finally, i found what i need : SFrame – Python

Resources you will need

• Graphlab library
• SFrame library

Example Code

Bill gate’s house import graphlab sf = graphlab.SFrame('Training.csv') my_features1 = ["features1","features2"] my_features_model = graphlab.linear_regression.create(sf,target='price',features=my_features1,validation_set=None) bill_gates = {                  'features1':0.49,                  'features2':0.18              } print my_features_model.predict(bill_gates) Done. I classify this challenge to become linear regression multi values. It’s my simple way to solve. Your simple some way?