The following pages link to Multi-class AdaBoost (Q119640):
Displaying 46 items.
- rbooster (Q119641) (← links)
- Boosting algorithms: regularization, prediction and model fitting (Q449780) (← 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)
- BoosTexter: A boosting-based system for text categorization (Q1568474) (← links)
- Probability estimation for multi-class classification using adaboost (Q1677008) (← links)
- Top-down decision tree learning as information based boosting (Q1870539) (← links)
- Boosting \(k\)-NN for categorization of natural scenes (Q1943405) (← links)
- Multiclass classification with bandit feedback using adaptive regularization (Q1945036) (← links)
- Multiclass boosting with adaptive group-based \(k\)NN and its application in text categorization (Q1955197) (← links)
- Improved boosting algorithms using confidence-rated predictions (Q1969321) (← 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)
- A coarse-to-fine approach for intelligent logging lithology identification with extremely randomized trees (Q2238076) (← links)
- Canonical forest (Q2259759) (← links)
- Boosting as a kernel-based method (Q2331677) (← links)
- Multi-class learning by smoothed boosting (Q2384151) (← links)
- Multicategory large margin classification methods: hinge losses vs. coherence functions (Q2510115) (← links)
- An improved multiclass LogitBoost using adaptive-one-vs-one (Q2514757) (← links)
- Multi-class boosting with asymmetric binary weak-learners (Q2629847) (← links)
- Reducing multiclass to binary: A unifying approach for margin classifiers (Q2782273) (← 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)
- A calibrated multiclass extension of AdaBoost (Q2921170) (← links)
- Online boosting algorithms based on exponential and 0-1 loss (Q2924383) (← links)
- MetaBayes: Bayesian Meta-Interpretative Learning Using Higher-Order Stochastic Refinement (Q2943874) (← links)
- Component-wise AdaBoost algorithms for high-dimensional binary classification and class probability prediction (Q3295738) (← links)
- Multiclass Probability Estimation With Support Vector Machines (Q3391267) (← links)
- Predictive decision making under risk and uncertainty: A support vector machines model (Q4603930) (← links)
- COST-SENSITIVE MULTI-CLASS ADABOOST FOR UNDERSTANDING DRIVING BEHAVIOR BASED ON TELEMATICS (Q5019037) (← links)
- (Q5214229) (← links)
- Transforming examples for multiclass boosting (Q5306316) (← 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)
- Algorithm selection on a meta level (Q6106469) (← links)
- An explained artificial intelligence-based solution to identify depression severity symptoms using acoustic features (Q6204286) (← links)
- An empirical study of a simple incremental classifier based on vector quantization and adaptive resonance theory (Q6567111) (← links)
- Multi-class imbalance problem: a multi-objective solution (Q6595325) (← links)
- A new integrated discrimination improvement index via odds (Q6640117) (← links)
- A boosting framework for positive-unlabeled learning (Q6657837) (← links)
