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https://issues.apache.org/jira/browse/MADLIB-1384?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank McQuillan closed MADLIB-1384.
-----------------------------------
Resolution: Fixed
https://github.com/apache/madlib/pull/448
> Change default num_components for SVM to max(100, 2*num_features)
> -----------------------------------------------------------------
>
> Key: MADLIB-1384
> URL: https://issues.apache.org/jira/browse/MADLIB-1384
> Project: Apache MADlib
> Issue Type: Improvement
> Components: Module: Support Vector Machines
> Reporter: Frank McQuillan
> Priority: Major
> Fix For: v1.17
>
>
> Currently
> http://madlib.apache.org/docs/latest/group__grp__svm.html#kernel_params
> says
> {code}
> n_components
> Default: 2*num_features. The dimensionality of the transformed feature space.
> A larger value lowers the variance of the estimate of the kernel but requires
> more memory and takes longer to train.
> {code}
> but this produces poor decision boundaries for small num_features. I suggest
> we change the default to
> {code}
> n_components
> Default: max(100, 2*num_features). The dimensionality of the transformed
> feature space. A larger value lowers the variance of the estimate of the
> kernel but requires more memory and takes longer to train.
> {code}
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