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[ML] Data Frame Analytics: Fix feature importance #61761

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merged 11 commits into from
Apr 4, 2020

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walterra
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@walterra walterra commented Mar 30, 2020

Summary

Fixes #55805

  • Fixes missing num_top_feature_importance_values parameter for analytics job configurations
  • Fixes analytics create form to consider feature importance
  • Fixes missing feature importance fields from results pages

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@walterra walterra added bug Fixes for quality problems that affect the customer experience release_note:fix :ml v8.0.0 Feature:Data Frame Analytics ML data frame analytics features v7.7.0 v7.8.0 labels Mar 30, 2020
@walterra walterra requested a review from a team as a code owner March 30, 2020 08:31
@walterra walterra self-assigned this Mar 30, 2020
@elasticmachine
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Pinging @elastic/ml-ui (:ml)

if (numTopFeatureImportanceValues > 0) {
featureImportanceFields.push(
...fields.map(d => ({
id: `${resultsField}.feature_importance.${d.id}`,
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This highlights that we need to use EuiDataGrid for classification and regression results, as I can't actually tell which columns are which!

image

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@alvarezmelissa87 alvarezmelissa87 left a comment

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LGTM ⚡️

@walterra
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walterra commented Apr 3, 2020

@peteharverson I fixed form validation, please have another look.

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💚 Build Succeeded

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To update your PR or re-run it, just comment with:
@elasticmachine merge upstream

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Tested latest edits and LGTM!

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Gave this a local test and latest LGTM ⚡️

@walterra walterra merged commit 8c06b12 into elastic:master Apr 4, 2020
@walterra walterra deleted the ml-fix-feature-importance branch April 4, 2020 07:36
walterra added a commit that referenced this pull request Apr 4, 2020
- Fixes missing num_top_feature_importance_values parameter for analytics job configurations
- Fixes analytics create form to consider feature importance
- Fixes missing feature importance fields from results pages
gmmorris added a commit to gmmorris/kibana that referenced this pull request Apr 6, 2020
…into event-log/query-support

* 'event-log/query-support' of github.com:gmmorris/kibana: (41 commits)
  [jenkins] refer to sizes in most pipeline code (elastic#62082)
  skip flaky suite (elastic#60470)
  [Discover] Fix flaky FT in field visualize (elastic#62418)
  [ML] Data Frame Analytics: Fix feature importance (elastic#61761)
  [Reporting] Use a shim for server config (elastic#62086)
  [Reporting] Fix reporting for non-default spaces (elastic#62226)
  Fix bug that coerced empty scaled float value to 0 (elastic#62251)
  [SIEM] [Detection Engine] Remove has manage api keys requireme… (elastic#62446)
  [Maps] Safely handle empty string and invalid strings from EuiColorPicker (elastic#62507)
  Reporting/bug more blacklisted headers (elastic#62389)
  [SIEM] Prevent undefined behavior in our ML popover (elastic#62498)
  [SIEM] [Detection Engine] remove all unknowns from all rules t… (elastic#62327)
  base changes for active/current node styling (elastic#62007)
  [kbn/ui-shared-deps] expand and split (elastic#62364)
  [ML] DF Analytics - ensure destination index pattern created (elastic#62450)
  Mark rule run as failure if there was an error (elastic#62383)
  Add docs for metric explorer alerts (elastic#62314)
  skip flaky suite (elastic#62281)
  [SIEM][Detection Engine] Fixes export of single rule and the icons
  fixes flakiness (elastic#62406)
  ...
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bug Fixes for quality problems that affect the customer experience Feature:Data Frame Analytics ML data frame analytics features :ml release_note:enhancement v7.8.0 v8.0.0
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[ML] DF Analytics results: Support for feature_importance
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