Catboost
PulseAugur coverage of Catboost — every cluster mentioning Catboost across labs, papers, and developer communities, ranked by signal.
-
Guide Explains Tree-Based Models From Decision Trees to Boosting
This article provides a guide to tree-based models, explaining their effectiveness with tabular data and their evolution from simple decision trees to advanced boosting algorithms like XGBoost, LightGBM, and CatBoost. I…
-
New benchmarks improve IBD classification using donor-aware scRNA-seq analysis
Researchers have developed a donor-aware benchmark for classifying Inflammatory Bowel Disease (IBD) using single-cell RNA sequencing (scRNA-seq) data. This new benchmark addresses the issue of pseudoreplication by ensur…
-
Manokhin Probability Matrix offers new framework for classifier quality
Researchers have introduced the Manokhin Probability Matrix, a new diagnostic framework designed to evaluate the quality of probabilistic predictions from classifiers. This framework separates reliability and resolution…
-
New 'Orange Book of Machine Learning' covers supervised regression and classification
A new book titled "The Orange Book of Machine Learning - Green edition" has been released, focusing on supervised regression and classification for tabular data. Authored by Carl McBride Ellis, the book covers essential…
-
ML models show difficulty forecasting volatile Australian electricity prices
A new study benchmarks six machine learning models for short-term electricity price forecasting in Australia's National Electricity Market. The research highlights significant challenges due to high price volatility, ir…
-
An Integrated Framework for Explainable, Fair, and Observable Hospital Readmission Prediction: Development and Validation on MIMIC-IV
Researchers have developed a new gradient-regularized Newton scheme to ensure global convergence for Gradient Boosting Decision Trees (GBDTs), a technique widely used in tabular machine learning. This method introduces …