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edit approved Oct 29, 2015 at 8:10
eliasah
edit approved Oct 29, 2015 at 8:10
eliasah
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Voting ( combined result )results from different classifiers gave bad accuracy

I used following classifiers along with their accuracies:

  1. Random forest - 85 %
  2. SVM - 78 %
  3. Adaboost - 82% 4 
  4. Logistic regression - 80%

When I used voting from above classifiers for final classification, I got lesser accuracy than the case when I used Random forest alone.

How is this possible? All classifiers are giving more or less same accuracies when used individually, then how does Random Forest outperform their combined result ?

Voting ( combined result ) from different classifiers gave bad accuracy

I used following classifiers along with their accuracies:

  1. Random forest - 85 %
  2. SVM - 78 %
  3. Adaboost - 82% 4 Logistic regression - 80%

When I used voting from above classifiers for final classification, I got lesser accuracy than the case when I used Random forest alone.

How is this possible? All classifiers are giving more or less same accuracies when used individually, then how does Random Forest outperform their combined result ?

Voting combined results from different classifiers gave bad accuracy

I used following classifiers along with their accuracies:

  1. Random forest - 85 %
  2. SVM - 78 %
  3. Adaboost - 82% 
  4. Logistic regression - 80%

When I used voting from above classifiers for final classification, I got lesser accuracy than the case when I used Random forest alone.

How is this possible? All classifiers are giving more or less same accuracies when used individually, then how does Random Forest outperform their combined result ?

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mach
mach
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Voting ( combined result ) from different classifiers gave bad accuracy

I used following classifiers along with their accuracies:

  1. Random forest - 85 %
  2. SVM - 78 %
  3. Adaboost - 82% 4 Logistic regression - 80%

When I used voting from above classifiers for final classification, I got lesser accuracy than the case when I used Random forest alone.

How is this possible? All classifiers are giving more or less same accuracies when used individually, then how does Random Forest outperform their combined result ?