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[Major] Comprehensive tests -- golden master and correctness #43

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ElizabethSantorellaQC opened this issue Apr 16, 2020 · 3 comments
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[Major] Comprehensive tests -- golden master and correctness #43

ElizabethSantorellaQC opened this issue Apr 16, 2020 · 3 comments
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@MarcAntoineSchmidtQC
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code quality this week's work we're doing it now

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@ElizabethSantorellaQC
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ElizabethSantorellaQC commented Apr 16, 2020 •
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  • Every feature in sklearn should be used in some golden master test, so we can make sure we aren't breaking anything, especially for less-used features like warm starts
  • We should also confirm the correctness of sklearn solutions, perhaps by perturbing parameter values at the estimated optimum. This could be slow so we might not want to build it into the test suite. This is especially needed for gamma and Tweedie with regularization. Jan is confident in these since they have been tested against other software, but not with regularization.
@ElizabethSantorellaQC ElizabethSantorellaQC changed the title [Major] Comprehensive tests [Major] Comprehensive tests -- golden master and correctness Apr 16, 2020
@ElizabethSantorellaQC ElizabethSantorellaQC added the this week's work we're doing it now label Apr 16, 2020
@tbenthompson
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some things that we're not testing right now:

  • variable penalties
  • warm starting
  • fitting with no intercept

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@ElizabethSantorellaQC
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See #101

@tbenthompson
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We now have a nice set of golden master tests from PR #101. See Issue #111 for ongoing work to ensure that we're converging in all possible cases.

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@tbenthompson @ElizabethSantorellaQC @MarcAntoineSchmidtQC