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[DOCS] Add ml-cpp PRs to 7.9.0 release notes (#60689) 

Co-authored-by: David Roberts <dave.roberts@elastic.co>
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Lisa Cawley 2020-08-05 10:12:11 -07:00 committed by GitHub
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@ -69,6 +69,7 @@ Geo::
Machine Learning::
* Add update data frame analytics jobs API {es-pull}58302[#58302] (issue: {es-issue}45720[#45720])
* Introduce model_plot_config.annotations_enabled setting for anomaly detection jobs {es-pull}57539[#57539] (issue: {es-issue}55781[#55781])
* Report significant changes to anomaly detection models in annotations of the results {ml-pull}1247[#1247], {es-pull}56342[#56342], {es-pull}56417[#56417], {es-pull}57144[#57144], {es-pull}57278[#57278], {es-pull}57539[#57539]
Mapping::
* Merge mappings for composable index templates {es-pull}58521[#58521] (issue: {es-issue}53101[#53101])
@ -184,6 +185,18 @@ Machine Learning::
* Delete auto-generated annotations when model snapshot is reverted {es-pull}58240[#58240] (issue: {es-issue}57982[#57982])
* Delete expired data by job {es-pull}57337[#57337]
* Introduce Annotation.event field {es-pull}57144[#57144] (issue: {es-issue}55781[#55781])
* Add support for larger forecasts in memory via max_model_memory setting {ml-pull}1238[#1238], {es-pull}57254[#57254]
* Don't lose precision when saving model state {ml-pull}1274[#1274]
* Parallelize the feature importance calculation for classification and regression over trees {ml-pull}1277[#1277]
* Add an option to do categorization independently for each partition {ml-pull}1293[#1293], {ml-pull}1318[#1318], {ml-pull}1356[#1356], {es-pull}57683[#57683]
* Memory usage is reported during job initialization {ml-pull}1294[#1294]
* More realistic memory estimation for classification and regression means that these analyses will require lower memory limits than before {ml-pull}1298[#1298]
* Checkpoint state to allow efficient failover during coarse parameter search for classification and regression {ml-pull}1300[#1300]
* Improve data access patterns to speed up classification and regression {ml-pull}1312[#1312]
* Performance improvements for classification and regression, particularly running multithreaded {ml-pull}1317[#1317]
* Improve runtime and memory usage training deep trees for classification and regression {ml-pull}1340[#1340]
* Improvement in handling large inference model definitions {ml-pull}1349[#1349]
* Add a peak_model_bytes field to model_size_stats {ml-pull}1389[#1389]
Mapping::
* Add regex query support to wildcard field {es-pull}55548[#55548] (issue: {es-issue}54725[#54725])
@ -290,6 +303,9 @@ Machine Learning::
* Fix wire serialization for flush acknowledgements {es-pull}58413[#58413]
* Make waiting for renormalization optional for internally flushing job {es-pull}58537[#58537] (issue: {es-issue}58395[#58395])
* Tail the C++ logging pipe before connecting other pipes {es-pull}56632[#56632] (issue: {es-issue}56366[#56366])
* Fix numerical issues leading to blow up of the model plot bounds {ml-pull}1268[#1268]
* Fix causes for inverted forecast confidence interval bounds {ml-pull}1369[#1369] (issue: {ml-issue}1357[#1357])
* Restrict growth of max matching string length for categories {ml-pull}1406[#1406]
Mapping::
* Wildcard field fix for scripts - changed value type from BytesRef to String {es-pull}58060[#58060] (issue: {es-issue}58044[#58044])
@ -314,5 +330,3 @@ Snapshot/Restore::
Search::
* Update to lucene snapshot e7c625430ed {es-pull}57981[#57981]