Weighted Voting Ensemble
Hello All,
I am doing a research on heterogeneous classifier ensembles to improve prediction accuracy. I have been searching to find weighted voting in rapid miner but unsuccessful. I have implemented simple majority voting using the Vote operator, but now I want to implement Weighted Voting. How can I do that ? If it's not built-in, then please let me know if any third party tool is available ?
Grateful
Farhan !
I am doing a research on heterogeneous classifier ensembles to improve prediction accuracy. I have been searching to find weighted voting in rapid miner but unsuccessful. I have implemented simple majority voting using the Vote operator, but now I want to implement Weighted Voting. How can I do that ? If it's not built-in, then please let me know if any third party tool is available ?
Grateful
Farhan !
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Hi,
unfortunately there is no single operator that can do it in one step. You have to create your own process for it. It will probably be relatively complex and include X-Validations to calculate the performance, joining together the results of the base learners and then manually aggregating and weighting the predictions.
What could be interesting is the Stacking approach, where you first create some base classifiers and then train a final model on the predictions of the base classifiers. It is expected that the final model will assign higher weights to those base classifiers that deliver better predictions.
Best regards,
Marius
unfortunately there is no single operator that can do it in one step. You have to create your own process for it. It will probably be relatively complex and include X-Validations to calculate the performance, joining together the results of the base learners and then manually aggregating and weighting the predictions.
What could be interesting is the Stacking approach, where you first create some base classifiers and then train a final model on the predictions of the base classifiers. It is expected that the final model will assign higher weights to those base classifiers that deliver better predictions.
Best regards,
Marius
which criteria should be used for weighting?
Best regards,
Marius