Chủ Nhật, 20 tháng 12, 2015

Predicting house prices

My fucking boss give me the fucking 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 Traning:

  • Content Traning.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 gates' 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?

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