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July 02, 2017
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A Benchmark of Open Source Tools for Machine Learning from R - UseR! 2017 Conference - Brussels, July, 2007

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szilard

July 02, 2017
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Transcript

  1. A Benchmark of Open Source Tools for Machine Learning from

    R Szilárd Pafka, PhD Chief Scientist, Epoch useR! 2017 Conference Brussels, July 2017
  2. None

  3. Disclaimer: I am not representing my employer (Epoch) in this

    talk I cannot confirm nor deny if Epoch is using any of the methods, tools, results etc. mentioned in this talk
  4. None
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  11. binary classification, 10M records numeric & categorical features, non-sparse

  12. http://www.cs.cornell.edu/~alexn/papers/empirical.icml06.pdf http://lowrank.net/nikos/pubs/empirical.pdf

  13. http://www.cs.cornell.edu/~alexn/papers/empirical.icml06.pdf http://lowrank.net/nikos/pubs/empirical.pdf

  14. None
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  18. EC2

  19. n = 10K, 100K, 1M, 10M, 100M Training time RAM

    usage AUC CPU % by core read data, pre-process, score test data

  20. n = 10K, 100K, 1M, 10M, 100M Training time RAM

    usage AUC CPU % by core read data, pre-process, score test data
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  28. 10x

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  34. http://datascience.la/benchmarking-random-forest-implementations/#comment-53599

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  41. Best linear: 71.1

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  44. learn_rate = 0.1, max_depth = 6, n_trees = 300 learn_rate

    = 0.01, max_depth = 16, n_trees = 1000
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  52. ...

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  64. R++

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