weka.classifiers.functions.SimpleLinearRegression

weka.classifiers.functions.SimpleLinearRegression 為簡單線性迴歸學習器，
簡單指的是只挑一個平方誤差最小的屬性作線性預測。
只適用數值對數值的預測，不接受缺值案例。

> java  weka.classifiers.functions.SimpleLinearRegression  -t data\cpu.arff


Linear regression on MMAX

0.01 * MMAX - 34


Time taken to build model: 0 seconds
Time taken to test model on training data: 0.02 seconds

=== Error on training data ===

Correlation coefficient                  0.863
Mean absolute error                     50.8658
Root mean squared error                 81.0566
Relative absolute error                 53.0319 %
Root relative squared error             50.5197 %
Total Number of Instances              209     



=== Cross-validation ===

Correlation coefficient                  0.7844
Mean absolute error                     53.8054
Root mean squared error                 99.5674
Relative absolute error                 55.908  %
Root relative squared error             61.8997 %
Total Number of Instances              209    

cpu.arff 資料集有209案例，每個案例由6個數值屬性預測1個數值屬性。


 


  
MYCT
  
MMIN
  
MMAX
  
CACH
  
CHMIN
  
CHMAX
  
class
 

  
125
  
256
  
6000
  
256
  
16
  
128
  
198
 

  
29
  
8000
  
32000
  
32
  
8
  
32
  
269
 

  
29
  
8000
  
32000
  
32
  
8
  
32
  
220
 

  
29
  
8000
  
32000
  
32
  
8
  
32
  
172
 

  
29
  
8000
  
16000
  
32
  
8
  
16
  
132
 

  
26
  
8000
  
32000
  
64
  
8
  
32
  
318
 

  
23
  
16000
  
32000
  
64
  
16
  
32
  
367
 

  
23
  
16000
  
32000
  
64
  
16
  
32
  
489
 

  
23
  
16000
  
64000
  
64
  
16
  
32
  
636
 

  
.....
  


  


  


  


  


  


 


參考:
1.weka.classifiers.functions.SimpleLinearRegression
   code | doc