Záznam dôkazov metódy

Semi-supervised CatBoost

Semi-supervised CatBoost applies CatBoost's ordered gradient boosting framework to settings where only a fraction of training instances carry labels, leveraging unlabeled data through pseudo-labeling or consistency-based strategies to improve model accuracy beyond what labeled data alone would allow.

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Semi-supervised CatBoost (Gradient Boosting with Partially Labeled Data)

Taxonomický záznam metódy · ml-model / machine-learning

Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A. V., & Gulin, A. (2018). CatBoost: unbiased boosting with categorical features. In Advances in Neural Information Processing Systems (NeurIPS), 31. · URL
Chapelle, O., Scholkopf, B., & Zien, A. (Eds.). (2006). Semi-Supervised Learning. MIT Press. · ISBN 978-0-262-03358-9

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Same method familyCatBoostmachine-suggested · Relational suggestion, not evidence.Same method familyGradient Boostingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSemi-supervised Gradient Boostingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSemi-supervised Random Forestmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSemi-supervised XGBoostmachine-suggested · Relational suggestion, not evidence.