Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

The easiest way to do this is using the ``Remove'' filter. Doing this from the explorer is easy, but if you want to do it programmatically, you should be careful. Make use of class ``weka.filters.unsupervised.attribute.Remove''. First set the attributes which have to be removed and then use the ``setInputFormat'' function to build the format of the output dataset, and then use the static function useFilter from the Filter class.

Source: Weka FAQ

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