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Remove Pearson correlation score based feature filtering for random effects #457
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@ashelkovnykov The migration to external artifact repo is done. Please update |
@cmjiang |
@ashelkovnykov Good question. We don't need to push each change to a new jar. And we definitely don't want to suddenly bump 5 major version up. However the problem is that the version is explicitly pinned in the |
Since we don't have to push each change to a new jar, we can just keep the same version number for those PRs without new jars. The problem is that the same version number may have different versions of code. |
@@ -287,27 +286,24 @@ object RandomEffectDataset { | |||
randomEffectDataConfiguration, | |||
randomEffectPartitioner) | |||
val projectedGroupedActiveData = generateProjectedActiveData(unfilteredActiveData, unfilteredProjectors) | |||
val projectedUnfilteredActiveData = featureSelectionOnActiveData( | |||
projectedGroupedActiveData, | |||
randomEffectDataConfiguration.numFeaturesToSamplesRatioUpperBound) |
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Forgot to remove the numFeaturesToSamplesRatioUpperBound
from the data configuration
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