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.

Package details

AuthorWannes Rosiers (InfoFarm)
MaintainerWannes Rosiers <>
Package repositoryView on CRAN
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parallelSVM documentation built on May 2, 2019, 9:32 a.m.