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.

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GBM Building Does Not Stop when Error Reaches 0 #11211

Open exalate-issue-sync[bot] opened 1 year ago

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

When trying a trivial example where the predictor is equal to the response, the first GBM model in the grid search will not stop training even after logloss has reached 0.

A reproducible example is attached.

{code}

Create Data - predictor is equal to response

iris_h2o <- as.h2o(iris) iris_h2o$C1 <- iris_h2o$Species iris_h2o <- iris_h2o[c("C1", "Species")]

Run AutoML

aml <- h2o.automl(response_column = "Species", training_frame = iris_h2o) {code}

h2o-ops commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-4678 Assignee: UNASSIGNED Reporter: Megan Kurka State: Open Fix Version: N/A Attachments: Available (Count: 2) Development PRs: N/A

Attachments From Jira

Attachment Name: AutoML_EarlyStoppingIssue.R Attached By: Megan Kurka File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-4678/AutoML_EarlyStoppingIssue.R

Attachment Name: Screen Shot 2017-04-20 at 3.22.05 PM.png Attached By: Megan Kurka File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-4678/Screen Shot 2017-04-20 at 3.22.05 PM.png