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[DOCS] Add ml-cpp PRs to 7.7 release notes (#55264)

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Co-Authored-By: David Roberts <dave.roberts@elastic.co>
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Lisa Cawley 2020-04-16 11:09:37 -07:00 committed by lcawl
parent d7cded8d7a
commit cf5278f771
1 changed files with 34 additions and 6 deletions
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docs/reference/release-notes/7.7.asciidoc
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@ -108,6 +108,9 @@ Infra/Packaging::
Machine Learning::
* Implement ILM policy for .ml-state* indices {pull}52356[#52356] (issue: {issue}29938[#29938])
* Add instrumentation to report statistics related to {dfanalytics-jobs} such as
progress, memory usage, etc. {ml-pull}906[#906]
* Multiclass classification {ml-pull}1037[#1037]
Mapping::
* Introduce a `constant_keyword` field. {pull}49713[#49713]
@ -283,8 +286,32 @@ Machine Learning::
* Add tags url param to GET {pull}51330[#51330]
* Add parsers for inference configuration classes {pull}51300[#51300]
* Make datafeeds work with nanosecond time fields {pull}51180[#51180] (issue: {issue}49889[#49889])
* Add audit warning for 1000 categories found early in job {pull}51146[#51146] (issue: {issue}50749[#50749])
* Adds support for a global calendars {pull}50372[#50372] (issue: {issue}45013[#45013])
* Speed up computation of feature importance
{ml-pull}1005[1005]
* Improve initialization of learn rate for better and more stable results in
regression and classification {ml-pull}948[#948]
* Add number of processed training samples to the definition of decision tree
nodes {ml-pull}991[#991]
* Add new model_size_stats fields to instrument categorization
{ml-pull}948[#948], {pull}51879[#51879] (issue: {issue}50794[#50749])
* Improve upfront memory estimation for all data frame analyses, which were
higher than necessary. This will improve the allocation of data frame analyses
to cluster nodes {ml-pull}1003[#1003]
* Upgrade the compiler used on Linux from gcc 7.3 to gcc 7.5, and the binutils
used in the build from version 2.20 to 2.34 {ml-pull}1013[#1013]
* Add instrumentation of the peak memory consumption for {dfanalytics-jobs}
{ml-pull}1022[#1022]
* Remove all memory overheads for computing tree SHAP values {ml-pull}1023[#1023]
* Distinguish between empty and missing categorical fields in classification and
regression model training {ml-pull}1034[#1034]
* Add instrumentation information for supervised learning {dfanalytics-jobs}
{ml-pull}1031[#1031]
* Add instrumentation information for {oldetection} data frame analytics jobs
{ml-pull}1068[#1068]
* Write out feature importance for multi-class models {ml-pull}1071[#1071]
* Enable system call filtering to the native process used with {dfanalytics}
{ml-pull}1098[#1098]
Mapping::
* Wildcard field - add normalizer support {pull}53851[#53851]
@ -493,16 +520,17 @@ Machine Learning::
* Perform evaluation in multiple steps when necessary {pull}53295[#53295]
* Specifying missing_field_value value and using it instead of empty_string {pull}53108[#53108] (issue: {issue}1034[#1034])
* Use event.timezone in ingest pipeline from find_file_structure {pull}52720[#52720] (issue: {issue}9458[#9458])
* Don't return inflated definition when storing trained models {pull}52573[#52573]
* Validate tree feature index is within range {pull}52460[#52460]
* Better error when persistent task assignment disabled {pull}52014[#52014] (issue: {issue}51956[#51956])
* Fix possible race condition starting datafeed {pull}51646[#51646] (issues: {issue}50886[#50886], {issue}51302[#51302])
* Fix 2 digit year regex in find_file_structure {pull}51469[#51469]
* Fix possible race condition when starting datafeed {pull}51302[#51302] (issue: {issue}51285[#51285])
* Validate classification dependent_variable cardinality is at least two {pull}51232[#51232]
* Do not copy mapping from dependent variable to prediction field in regression analysis {pull}51227[#51227]
* Address two edge cases for categorization.GrokPatternCreator#findBestGrokMatchFromExamples {pull}51168[#51168]
* Calculate results and snapshot retention using latest bucket timestamps {pull}51061[#51061]
* Use largest ordered subset of categorization tokens for category reverse
search regex {ml-pull}970[#970] (issue: {ml-issue}949[#949])
* Account for the data frame's memory when estimating the peak memory used by
classification and regression model training {ml-pull}996[#996]
* Rename classification and regression parameter maximum_number_trees to
max_trees {ml-pull}1047[#1047]
Mapping::
* Throw better exception on wrong `dynamic_templates` syntax {pull}51783[#51783] (issue: {issue}51486[#51486])