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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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h2o.confusionMatrix() does not support the standard train and xval arguments in R #8483

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

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

This seems broken to me. Like all the other metrics functions, we should have a train, valid and xval argument, but the only one working here is valid. We need to support those.

{code:java}

gbm <- h2o.gbm(y = "Species", training_frame = as.h2o(iris), validation_frame = as.h2o(iris), nfolds = 3) |=========================================================================================================================| 100% |=========================================================================================================================| 100% |=========================================================================================================================| 100% h2o.confusionMatrix(gbm, train = TRUE) Error in .local(object, ...) : unused argument (train = TRUE) h2o.confusionMatrix(gbm, valid = TRUE) Confusion Matrix: Row labels: Actual class; Column labels: Predicted class setosa versicolor virginica Error Rate setosa 50 0 0 0.0000 = 0 / 50 versicolor 0 50 0 0.0000 = 0 / 50 virginica 0 0 50 0.0000 = 0 / 50 Totals 50 50 50 0.0000 = 0 / 150 h2o.confusionMatrix(gbm, xval = TRUE) Error in .local(object, ...) : unused argument (xval = TRUE) {code}

h2o-ops commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-7156 Assignee: Michal Kurka Reporter: Erin LeDell State: In Progress Fix Version: N/A Attachments: N/A Development PRs: N/A