I have trained random forest using Weka for a regression problem. I want to calculate the prediction interval without using Bagging and RegressionByDiscretization. Is there a way to get the prediction interval from the random forest? If not, is it possible to train random forest using Bagging and RegressionByDiscretization and get the same error rate as when training the random forest without Bagging and RegressionByDiscretization?
Is the IB1 classifier simply the IBk classifier with k=1?
I tried to use it in a Java program. The IDE I use (Eclipse) can't find it in the weka.jar (3.9.5). And when I look into the jar file, in particular the weka.classifiers.lazy tree, there is no IB1 reference.
Joe McVerry - 919.846.2014
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Is there a way to grab the feature importance/variables importance from Weka classifiers, which is similar to scikit-learn of python?
I briefly searched around by Google, which seems ClassifierAttributeEval function is close to what I expect, but I am not sure how to use it on groovy from the documentation (https://weka.sourceforge.io/doc.dev/weka/attributeSelection/ClassifierAttri…). It will be great to have any example of it for reference.
Thanks a lot!
Dear Weka developers,
I'm currently working on my undergraduate thesis here on UFF/Brazil and it is basically a comparison between Weka and SKLearn using the multilayer perceptron.
Right now i'm researching about the references used to built the MLP class on both tools. I already finded for the SKLearn, but i couldn't find it for Weka.
I already took a look at the documentation and source code, but still couldn't find the references, can you guys help me with this?
It has been a great experience to spend some time studying your tool to get my university degree!
Matheus Baldas Wandermurem.