I’m using the random forest classifier in Weka. When the algorithm selects the best feature for a tree node based on the
class impurity measure, it calculates the information (entropy) of the class for each value of a categorical feature, in my case I have only binary features.
It then computes the class impurity measure based on a weighted sum of those information values, where the weight for each feature value is given by the relative
frequency of that feature value in the dataset. I want to modify the calculation of that weight for each feature value, but I cannot find the part of the code where that weight is calculated. Can you please tell me which part of the code handles this? _______________________________________________ Wekalist mailing list -- [hidden email] Send posts to [hidden email] To unsubscribe send an email to [hidden email] To subscribe, unsubscribe, etc., visit https://list.waikato.ac.nz/postorius/lists/wekalist.list.waikato.ac.nz List etiquette: http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html |
> I’m using the random forest classifier in Weka. When the algorithm selects the best feature for a tree node based on the class impurity measure, it calculates the information (entropy) of the class for each value of a categorical feature, in my case I have only binary features. It then computes the class impurity measure based on a weighted sum of those information values, where the weight for each feature value is given by the relative frequency of that feature value in the dataset.
> > I want to modify the calculation of that weight for each feature value, but I cannot find the part of the code where that weight is calculated. > > Can you please tell me which part of the code handles this? RandomForest uses RandomTree as the base classifier for its forest. Have a look at that class. Cheers, Peter -- Peter Reutemann Dept. of Computer Science University of Waikato, NZ +64 (7) 577-5304 http://www.cms.waikato.ac.nz/~fracpete/ http://www.data-mining.co.nz/ _______________________________________________ Wekalist mailing list -- [hidden email] Send posts to [hidden email] To unsubscribe send an email to [hidden email] To subscribe, unsubscribe, etc., visit https://list.waikato.ac.nz/postorius/lists/wekalist.list.waikato.ac.nz List etiquette: http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html |
> RandomForest uses RandomTree as the base classifier for its forest. Thank you for the help Peter, I went back over the code and found it, I must have missed it the first time. If I may ask another question, once I have changed the code, how do I then implement that into the full version of Weka on my system? Thanks, Nate From: [hidden email] > I’m using the random forest classifier in Weka. When the algorithm selects the best feature for a tree node based on the class impurity measure, it calculates the information (entropy) of the class for each value of a categorical feature,
in my case I have only binary features. It then computes the class impurity measure based on a weighted sum of those information values, where the weight for each feature value is given by the relative frequency of that feature value in the dataset. _______________________________________________ Wekalist mailing list -- [hidden email] Send posts to [hidden email] To unsubscribe send an email to [hidden email] To subscribe, unsubscribe, etc., visit https://list.waikato.ac.nz/postorius/lists/wekalist.list.waikato.ac.nz List etiquette: http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html |
> > RandomForest uses RandomTree as the base classifier for its forest.
> > Have a look at that class. > > Thank you for the help Peter, I went back over the code and found it, I must have missed it the first time. Cool! > If I may ask another question, once I have changed the code, how do I then implement that into the full version of Weka on my system? Every download of Weka comes with a source jar (weka-src.jar) that contains the complete code and build scripts. Change the RandomTree code in that source tree and then compile the code base with ant: https://waikato.github.io/weka-wiki/compiling_weka/ Then just use the weka.jar from the "dist" directory. Cheers, Peter -- Peter Reutemann Dept. of Computer Science University of Waikato, NZ +64 (7) 577-5304 http://www.cms.waikato.ac.nz/~fracpete/ http://www.data-mining.co.nz/ _______________________________________________ Wekalist mailing list -- [hidden email] Send posts to [hidden email] To unsubscribe send an email to [hidden email] To subscribe, unsubscribe, etc., visit https://list.waikato.ac.nz/postorius/lists/wekalist.list.waikato.ac.nz List etiquette: http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html |
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