parallelSVM: A Parallel-Voting Version of the Support-Vector-Machine Algorithm

By sampling your data, running the Support-Vector-Machine algorithm on these samples in parallel on your own machine and letting your models vote on a prediction, we return much faster predictions than the regular Support-Vector-Machine and possibly even more accurate predictions.

Install the latest version of this package by entering the following in R:
AuthorWannes Rosiers (InfoFarm)
Date of publication2015-06-26 13:34:36
MaintainerWannes Rosiers <>

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