The following pages link to AdaBoost-SAMME (Q30964):
Displaying 27 items.
- Multi-class AdaBoost (Q119640) (← links)
- On hybrid classification using model assisted posterior estimates (Q408060) (← links)
- A weight-adjusted voting algorithm for ensembles of classifiers (Q743769) (← links)
- Soft-max boosting (Q747255) (← links)
- Mathematical optimization in classification and regression trees (Q828748) (← links)
- Angle-based cost-sensitive multicategory classification (Q830425) (← links)
- Probability estimation for multi-class classification using adaboost (Q1677008) (← links)
- Boosting \(k\)-NN for categorization of natural scenes (Q1943405) (← links)
- pBO-2GP-3B: a batch parallel known/unknown constrained Bayesian optimization with feasibility classification and its applications in computational fluid dynamics (Q1987855) (← links)
- Ensemble feature selection using election methods and ranker clustering (Q2004741) (← links)
- Data driven design for online industrial auctions (Q2043444) (← links)
- Multivariate deep learning model with ensemble pruning for time series forecasting (Q2079938) (← links)
- Double random forest (Q2203331) (← links)
- Fast greedy \(\mathcal{C} \)-bound minimization with guarantees (Q2217455) (← links)
- A coarse-to-fine approach for intelligent logging lithology identification with extremely randomized trees (Q2238076) (← links)
- Enhanced aspect-based sentiment analysis models with progressive self-supervised attention learning (Q2238585) (← links)
- Canonical forest (Q2259759) (← links)
- Boosting as a kernel-based method (Q2331677) (← links)
- Multicategory large margin classification methods: hinge losses vs. coherence functions (Q2510115) (← links)
- Multi-class boosting with asymmetric binary weak-learners (Q2629847) (← links)
- On the characterization of a class of Fisher-consistent loss functions and its application to boosting (Q2810880) (← links)
- Reversible Data Hiding for Encrypted Images Based on Statistical Learning (Q2817462) (← links)
- Multiclass Probability Estimation With Support Vector Machines (Q3391267) (← links)
- Predictive decision making under risk and uncertainty: A support vector machines model (Q4603930) (← links)
- A boosting inspired personalized threshold method for sepsis screening (Q5861518) (← links)
- AdaBoost Semiparametric Model Averaging Prediction for Multiple Categories (Q5881103) (← links)
- Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data (Q5881147) (← links)
