Gradient Boosting Machine: A Survey
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Summary
In this survey, several different types of gradient boosting algorithms are discussed and their mathematical frameworks are illustrated in detail.
- Type
- preprint
- Published
- 2019-08-19
- Cited by
- 59
- References
- 18
- Access
- Open access
- OpenAlex
- https://openalex.org/W2967733078
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:201070042
Keywords
Gradient boosting, Boosting (machine learning), Artificial intelligence, Computer science, Machine learning
References
- Special Invited Paper-Additive logistic regression: A statistical view of boosting
- Logistic Regression, AdaBoost and Bregman Distances
- Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost
- Boosting Algorithms as Gradient Descent in Function Space
- Greedy function approximation: A gradient boosting machine.
- A decision-theoretic generalization of on-line learning and an application to boosting
- Stochastic gradient boosting
- AdaBoost for Feature Selection, Classification and Its Relation with SVM, A Review
- Gradient boosting machines, a tutorial
- The Strength of Weak Learnability
- A General Boosting Method and its Application to Learning Ranking Functions for Web Search
- Boosting Algorithms as Gradient Descent
- AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problem
- A working guide to boosted regression trees.
- Quantile Regression
- Ranking, Boosting, and Model Adaptation
- Bias, Variance , And Arcing Classifiers
- Noname manuscript No. (will be inserted by the editor) Ranking, Boosting, and Model Adaptation
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- Interpretable ensembles of hyper-rectangles as base models
- Analysis Factors Affecting Egyptian Inflation Based on Machine Learning Algorithms
- Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach
- Teaching Language Models to Self-Improve through Interactive Demonstrations
- Data-Driven Modelling of Mobile Network Demand for Efficient Spectrum Management
- An improvement of the CNN-XGboost model for pneumonia disease classification
- Trustworthy AI: Deciding What to Decide
- Classification and Sizing of Surface Defects in Pipelines Based on the Results of Combined Diagnostics by Ultrasonic, Eddy Current, and Visual Inspection Methods of Nondestructive Testing
- Modeling Ionospheric TEC Using Gradient Boosting Based and Stacking Machine Learning Techniques
- Applying Artificial Intelligence to Support the Detection and Treatment of Melasma
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- Interplay of traditional methods and machine learning algorithms for tagging boosted objects
- SqueezeNet Feature Extraction dan Gradient Boosting untuk Klasifikasi Penyakit Monkeypox pada Citra Kulit
- Computational analysis of controlled drug release from porous polymeric carrier with the aid of Mass transfer and Artificial Intelligence modeling