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Customize Random-Forest Operator for average instead of simple vote
Learner III
Hi,
I want to use the Random-Forest Operator as a classifier. I have two different classes and I need to calculate the probabilites for Class 1. Because these probabilites are very low, I need the Random-Forest Operator to not just do a simple vote but to calculate an average of the individual trees.
The Random-Forest Operator does not have a parameter to choose for simple-vote/average.
Ideas, that did not work:
- I used Random-Tree-Operator within Vote-Operator. The operator manual says the Vote-Operator is capable of calculating an average instead of doing a simple vote, but only if I use a regression Classifier. The Random-Tree Operator has a confidence attribute as an output, but the Vote-Operator just does the simple vote. Again, there is no parameter to choose between simple vote and average.
Does anyone have an idea how to get the average instead of the simple vote? Maybe how to customize the existing Random-Forest-Operator or the Vote-Operator?
Greetings and thanks,
Jasmin
I want to use the Random-Forest Operator as a classifier. I have two different classes and I need to calculate the probabilites for Class 1. Because these probabilites are very low, I need the Random-Forest Operator to not just do a simple vote but to calculate an average of the individual trees.
The Random-Forest Operator does not have a parameter to choose for simple-vote/average.
Ideas, that did not work:
- I used Random-Tree-Operator within Vote-Operator. The operator manual says the Vote-Operator is capable of calculating an average instead of doing a simple vote, but only if I use a regression Classifier. The Random-Tree Operator has a confidence attribute as an output, but the Vote-Operator just does the simple vote. Again, there is no parameter to choose between simple vote and average.
Does anyone have an idea how to get the average instead of the simple vote? Maybe how to customize the existing Random-Forest-Operator or the Vote-Operator?
Greetings and thanks,
Jasmin
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