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RandomSearch :

Performs a Random search in the space of attribute subsets. If no start set is supplied, Random search starts from a random point and reports the best subset found. If a start set is supplied, Random searches randomly for subsets that are as good or better than the start point with the same or or fewer attributes. Using RandomSearch in conjunction with a start set containing all attributes equates to the LVF algorithm of Liu and Setiono (ICML-96).

For more information see:

H. Liu, R. Setiono: A probabilistic approach to feature selection - A filter solution. In: 13th International Conference on Machine Learning, 319-327, 1996.

Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (attributeSelectionSearchMethods)


The table below describes the options available for RandomSearch.




Percentage of the search space to explore.


Set the start point for the search. This is specified as a comma seperated list off attribute indexes starting at 1. It can include ranges. Eg. 1,2,5-9,17. If specified, Random searches for subsets of attributes that are as good as or better than the start set with the same or lower cardinality.


Print progress information. Sends progress info to the terminal as the search progresses.

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