Search code examples
javamodelclassificationwekatraining-data

Creating Weka classifier model without evaluation

I am trying to use java to feed a training dataset to Weka and get the model as output.

Found this instruction in Weka wiki:

You save a trained classifier with the -d option (dumping), e.g.:

java weka.classifiers.trees.J48 -t /some/where/train.arff -d /other/place/j48.model

The problem is when I use the mentioned command it first builds the model (takes seconds) and then it evaluates the data using 10-fold cross validation method, which takes minutes and is not needed.

The question is how can use weka to model the data for me without evaluating it.

Solution 
  • java weka.classifiers.trees.J48 -no-cv -t /some/where/train.arff -d /other/place/j48.model

    How I got there:

    java weka.classifiers.trees.J48 --help

    lists the available options, among others:

    -no-cv        Do not perform any cross validation.

    So when I use your command and add the -no-cv flag, that seems to do what you want.