search

h2oai / h2o-3

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
http://h2o.ai
Apache License 2.0
6.92k stars 2k forks source link

Upgrade XGBoost to 1.6 #7630

Closed exalate-issue-sync[bot] closed 1 year ago

exalate-issue-sync[bot] commented 1 year ago

(description in this Jira is related to XGBoost 1.3)

work started by [~accountid:5bd82be4216ccf49622e5137] but was not finished because of regression in XGB Performance on extermely sparse datasets (cox2 perf tests) for cox2-small scoring this was mitigated with limiting native scoring to 1 thread however training with full cox2 datasets is still much slower than with 1.2

PR: [https://github.com/h2oai/xgboost/pull/91|https://github.com/h2oai/xgboost/pull/91] PR(core): [https://github.com/h2oai/h2o-3/pull/5188/files|https://github.com/h2oai/h2o-3/pull/5188/files] BUILD: [http://jenkins:8080/view/H2O-3/job/h2o-3-xgboost4j-release-pipeline/job/honza%252Fmerge_1.3.0/|http://jenkins:8080/view/H2O-3/job/h2o-3-xgboost4j-release-pipeline/job/honza%252Fmerge_1.3.0/]

XGboost Issue [https://github.com/dmlc/xgboost/issues/6659|https://github.com/dmlc/xgboost/issues/6659|smart-link]

h2o-ops commented 1 year ago

JIRA Issue Details

Jira Issue: PUBDEV-8018 Assignee: Adam Valenta Reporter: Adam Valenta State: In Progress Fix Version: 3.42.0.1 Attachments: N/A Development PRs: Available

h2o-ops commented 1 year ago

Linked PRs from JIRA

https://github.com/h2oai/h2o-3/pull/6664 https://github.com/h2oai/h2o-3/pull/6704 https://github.com/h2oai/h2o-3/pull/6705

valenad1 commented 1 year ago

Implemented and part of 3.42