RandomSearch (original) (raw)

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.

BibTeX:

@inproceedings{Liu1996, author = {H. Liu and R. Setiono}, booktitle = {13th International Conference on Machine Learning}, pages = {319-327}, title = {A probabilistic approach to feature selection - A filter solution}, year = {1996} }

Valid options are:

-P Specify a starting set of attributes. Eg. 1,3,5-7. If a start point is supplied, random search evaluates the start point and then randomly looks for subsets that are as good as or better than the start point with the same or lower cardinality.

-F Percent of search space to consider. (default = 25%).

-V Output subsets as the search progresses. (default = false).

-seed Random seed (default = 1)