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Weka is a famous machine learning library in Java.

This repository will show how to run several algorithms on one dataset through weka.

Ouput of Test.java:

RandomForest
Evaluation: 
Correctly Classified Instances        8124              100      %
Incorrectly Classified Instances         0                0      %
Kappa statistic                          1     
K&B Relative Info Score                 99.949  %
K&B Information Score                 8112.2893 bits      0.9986 bits/instance
Class complexity | order 0            8116.4288 bits      0.9991 bits/instance
Class complexity | scheme                4.1394 bits      0.0005 bits/instance
Complexity improvement     (Sf)       8112.2893 bits      0.9986 bits/instance
Mean absolute error                      0.0003
Root mean squared error                  0.0031
Relative absolute error                  0.0697 %
Root relative squared error              0.627  %
Total Number of Instances             8124     


AdaBoostM1
Evaluation: 
Correctly Classified Instances        7825               96.3195 %
Incorrectly Classified Instances       299                3.6805 %
Kappa statistic                          0.9263
K&B Relative Info Score                 89.4359 %
K&B Information Score                 7259.0037 bits      0.8935 bits/instance
Class complexity | order 0            8116.4288 bits      0.9991 bits/instance
Class complexity | scheme             1054.2737 bits      0.1298 bits/instance
Complexity improvement     (Sf)       7062.1551 bits      0.8693 bits/instance
Mean absolute error                      0.0579
Root mean squared error                  0.1591
Relative absolute error                 11.5915 %
Root relative squared error             31.8497 %
Total Number of Instances             8124     


IBk
Evaluation: 
Correctly Classified Instances        8124              100      %
Incorrectly Classified Instances         0                0      %
Kappa statistic                          1     
K&B Relative Info Score                 99.9979 %
K&B Information Score                 8116.2603 bits      0.999  bits/instance
Class complexity | order 0            8116.4288 bits      0.9991 bits/instance
Class complexity | scheme                0.1684 bits      0      bits/instance
Complexity improvement     (Sf)       8116.2603 bits      0.999  bits/instance
Mean absolute error                      0     
Root mean squared error                  0     
Relative absolute error                  0.0029 %
Root relative squared error              0.003  %
Total Number of Instances             8124     


SMO
Evaluation: 
Correctly Classified Instances        8124              100      %
Incorrectly Classified Instances         0                0      %
Kappa statistic                          1     
K&B Relative Info Score                100      %
K&B Information Score                 8116.4288 bits      0.9991 bits/instance
Class complexity | order 0            8116.4288 bits      0.9991 bits/instance
Class complexity | scheme                0      bits      0      bits/instance
Complexity improvement     (Sf)       8116.4288 bits      0.9991 bits/instance
Mean absolute error                      0     
Root mean squared error                  0     
Relative absolute error                  0      %
Root relative squared error              0      %
Total Number of Instances             8124     


NaiveBayes
Evaluation: 
Correctly Classified Instances        7782               95.7903 %
Incorrectly Classified Instances       342                4.2097 %
Kappa statistic                          0.9155
K&B Relative Info Score                 91.6144 %
K&B Information Score                 7435.8151 bits      0.9153 bits/instance
Class complexity | order 0            8116.4288 bits      0.9991 bits/instance
Class complexity | scheme             1418.3394 bits      0.1746 bits/instance
Complexity improvement     (Sf)       6698.0893 bits      0.8245 bits/instance
Mean absolute error                      0.0418
Root mean squared error                  0.1756
Relative absolute error                  8.3755 %
Root relative squared error             35.1473 %
Total Number of Instances             8124     


LogitBoost
Evaluation: 
Correctly Classified Instances        7984               98.2767 %
Incorrectly Classified Instances       140                1.7233 %
Kappa statistic                          0.9655
K&B Relative Info Score                 91.0257 %
K&B Information Score                 7388.0397 bits      0.9094 bits/instance
Class complexity | order 0            8116.4288 bits      0.9991 bits/instance
Class complexity | scheme              811.6813 bits      0.0999 bits/instance
Complexity improvement     (Sf)       7304.7475 bits      0.8992 bits/instance
Mean absolute error                      0.0534
Root mean squared error                  0.1215
Relative absolute error                 10.6995 %
Root relative squared error             24.3116 %
Total Number of Instances             8124     

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