@@ -154,7 +154,24 @@ Machine Learning::
154
154
* Add lazy assignment job config option {pull}47726[#47726]
155
155
* Additional outlier detection parameters {pull}47600[#47600]
156
156
* More accurate job memory overhead {pull}47516[#47516]
157
- * Throttle the delete-by-query of expired results {pull}47177[#47177] (issues: {issue}47003[#47003], {issue}47103[#47103])
157
+ * Throttle the delete-by-query of expired results {pull}47177[#47177] (issue: {issue}47003[#47003])
158
+ * Improve performance and concurrency training boosted tree regression models.
159
+ For large data sets, this change was observed to give a 10% to 20% decrease in
160
+ train time. {ml-pull}622[#622]
161
+ * Upgrade Boost libraries to version 1.71 {ml-pull}638[#638]
162
+ * Improve initialisation of boosted tree training. This generally enables us to
163
+ find lower loss models faster. {ml-pull}686[#686]
164
+ * Include a smooth tree depth based penalty to regularized objective function for
165
+ boosted tree training. Hard depth based regularization is often the strategy of
166
+ choice to prevent over fitting for XGBoost. By smoothing, we can make better tradeoffs.
167
+ Also, the parameters of the penalty function are more suited to optimising with our
168
+ Bayesian optimisation based hyperparameter search. {ml-pull}698[#698]
169
+ * Binomial logistic regression targeting cross entropy {ml-pull}713[#713]
170
+ * Improvements to count and sum anomaly detection for sparse data. This primarily
171
+ aims to improve handling of data which are predictably present: detecting when they
172
+ are unexpectedly missing. {ml-pull}721[#721]
173
+ * Trap numeric errors causing bad hyperparameter search initialisation and repeated
174
+ errors to be logged during boosted tree training {ml-pull}732[#732]
158
175
159
176
Mapping::
160
177
* Add migration tool checks for _field_names disabling {pull}46972[#46972] (issues: {issue}42854[#42854], {issue}46681[#46681])
@@ -317,12 +334,14 @@ MULTIPLE AREA LABELS::
317
334
* Fix cluster alert for watcher/monitoring IndexOutOfBoundsExcep… {pull}45308[#45308] (issue: {issue}43184[#43184])
318
335
319
336
Machine Learning::
320
- * Deduplicate multi-fields for data frame analytics {pull}48799[#48799] (issues : {issue}48756[#48756], {issue}48770[#48770 ])
337
+ * Deduplicate multi-fields for data frame analytics {pull}48799[#48799] (issue : {issue}48756[#48756])
321
338
* Prevent fetching multi-field from source {pull}48770[#48770] (issue: {issue}48756[#48756])
322
339
* Fix detection of syslog-like timestamp in find_file_structure {pull}47970[#47970]
323
340
* Fix serialization of evaluation response. {pull}47557[#47557]
324
341
* Reinstate ML daily maintenance actions {pull}47103[#47103] (issue: {issue}47003[#47003])
325
342
* Fix two datafeed flush lockup bugs {pull}46982[#46982]
343
+ * Restore from checkpoint could damage seasonality modeling. For example, it could
344
+ cause seasonal components to be overwritten in error. {ml-pull}821[#821]
326
345
327
346
NOT CLASSIFIED::
328
347
* Remove uniqueness constraint for API key name and make it optional {pull}47549[#47549] (issue: {issue}46646[#46646])
@@ -383,7 +402,6 @@ Task Management::
383
402
Transform::
384
403
* Do not fail checkpoint creation due to global checkpoint mismatch {pull}48423[#48423] (issue: {issue}48379[#48379])
385
404
* Prevent assignment if any node is older than 7.4 {pull}48055[#48055] (issue: {issue}48019[#48019])
386
- * Prevent assignment to nodes older than 7.4 {pull}48044[#48044] (issue: {issue}48019[#48019])
387
405
* Fix bwc serialization with 7.3 {pull}48021[#48021]
388
406
* Signal listener early on task _stop failure {pull}47954[#47954]
389
407
* Use field_caps API for mapping deduction {pull}46703[#46703] (issue: {issue}46694[#46694])
0 commit comments