UnderBagging Testing in Matlab












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I used UnderBagging for an imbalanced dataset with 45700 observation with 20 fetures. 45000 observations are 1 and 700 are 0.
I used UnderBagging for classifier C ( for example for Decision Tree). I kept the 700 "one" observations and selected randomly 700 observations from zero dataset for 500 times. So I have 500 balanced datasets each with 1400 observation. I applied Decision Tree (MATLAB fitctree) for each. How can I select test dataset for evaluating the performance? For each sub-dataset from 500 datasets I must select randomly the test datasets? or I must before classification, select unseen test dataset from 45700 observations which is imbalance? Also how can I calculate confusion matrix?









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    I used UnderBagging for an imbalanced dataset with 45700 observation with 20 fetures. 45000 observations are 1 and 700 are 0.
    I used UnderBagging for classifier C ( for example for Decision Tree). I kept the 700 "one" observations and selected randomly 700 observations from zero dataset for 500 times. So I have 500 balanced datasets each with 1400 observation. I applied Decision Tree (MATLAB fitctree) for each. How can I select test dataset for evaluating the performance? For each sub-dataset from 500 datasets I must select randomly the test datasets? or I must before classification, select unseen test dataset from 45700 observations which is imbalance? Also how can I calculate confusion matrix?









    share







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    Morteza is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      $begingroup$


      I used UnderBagging for an imbalanced dataset with 45700 observation with 20 fetures. 45000 observations are 1 and 700 are 0.
      I used UnderBagging for classifier C ( for example for Decision Tree). I kept the 700 "one" observations and selected randomly 700 observations from zero dataset for 500 times. So I have 500 balanced datasets each with 1400 observation. I applied Decision Tree (MATLAB fitctree) for each. How can I select test dataset for evaluating the performance? For each sub-dataset from 500 datasets I must select randomly the test datasets? or I must before classification, select unseen test dataset from 45700 observations which is imbalance? Also how can I calculate confusion matrix?









      share







      New contributor




      Morteza is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I used UnderBagging for an imbalanced dataset with 45700 observation with 20 fetures. 45000 observations are 1 and 700 are 0.
      I used UnderBagging for classifier C ( for example for Decision Tree). I kept the 700 "one" observations and selected randomly 700 observations from zero dataset for 500 times. So I have 500 balanced datasets each with 1400 observation. I applied Decision Tree (MATLAB fitctree) for each. How can I select test dataset for evaluating the performance? For each sub-dataset from 500 datasets I must select randomly the test datasets? or I must before classification, select unseen test dataset from 45700 observations which is imbalance? Also how can I calculate confusion matrix?







      decision-trees matlab class-imbalance ensemble-learning





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