[MLLIB][WIP] SPARK-4638: Kernels feature for MLLIB #5503
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mandar2812
commented
Apr 14, 2015
mandar2812
commented
- Class hierarchy for SVM Kernels, with unit tests.
- Entropy based subset selection for low rank approximation of Large Kernel Matrices, with unit tests.
- Kernels for density estimation, with 'plug in' based optimum bandwidth selection, with unit tests.
…mentation of the Nystrom method for feature map extractions, RBF and Polynomial Kernels. Also a bare bones test suite for SVM Kernels is included
…ation 2) Code indentation changes
…mentation of the Nystrom method for feature map extractions, RBF and Polynomial Kernels. Also a bare bones test suite for SVM Kernels is included
…ation 2) Code indentation changes
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@dbtsai @mandar2812 I found the abstraction for kernel as explained in my PR #6213 more generic in practical use-cases compared to the usual interface available in scikit-learn...It will be great if we can come up with a strategy such that this PR calls IndexedRowMatrix.rowSimilarity to get the kernel from the data as represented with RDD[LabeledPoint] |
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jenkins, ok to test |
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Test build #37924 has finished for PR 5503 at commit
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Making scala style changes and optimizations and updating pull request asap |
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jenkins, ok to test |
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Test build #44747 has finished for PR 5503 at commit
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@mandar2812 any status on this PR? |
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Yes, I will update this PR by the 20th of December 2015. |
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I'm going to close this pull request. If this is still relevant and you are interested in pushing it forward, please open a new pull request. Thanks! |
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What is the result of this pull request? I can't seem to find the code in the code base anywhere |
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It didn't make it into spark. Instead I started the DynaML project and made kernels a key module of it, along with spark support. |
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