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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.
Getting started
Browse package contents
Package details |
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| Author | Wannes Rosiers (InfoFarm) |
| Maintainer | Wannes Rosiers <wannes.rosiers@infofarm.be> |
| License | GPL-2 |
| Version | 0.1-9 |
| URL | www.infofarm.be |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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