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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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Fix broken link in target encoding section #12933

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

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

the link at the bottom of our target encoding [section|http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-munging/target-encoding.html] for Preprocessing Scheme for High-Cardinality Categorical Columns is broken. We should update this with a stable link.

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

Angela Bartz commented: Note that this is also broken in the tutorial: https://github.com/h2oai/h2o-tutorials/blob/master/best-practices/categorical-predictors/target_encoding.md

If a new link can't be found, replace the link with a cited reference: Daniele Micci-Barreca. 2001. A preprocessing scheme for high-cardinality categorical attributes in classification and prediction problems. SIGKDD Explor. Newsl. 3, 1 (July 2001), 27-32.

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

Angela Bartz commented: Fixed link in the tutorial: https://github.com/h2oai/h2o-tutorials/blob/master/best-practices/categorical-predictors/target_encoding.md

For the User Guide update, this is fixed as part of pull request https://github.com/h2oai/h2o-3/pull/3066, which adds Python examples to the Target Encoding topic. (See PUBDEV-6040.)

hasithjp commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-6094 Assignee: Angela Bartz Reporter: Lauren DiPerna State: Resolved Fix Version: N/A Attachments: N/A Development PRs: N/A