https://github.com/dhruvsrikanth/boosting-theory
A collection of papers produced on the theory of boosting as applied to binary classification. Further extensions to the multi-class classification problem and necessary and sufficient conditions to ensure boostability i.e. weak learning conditions. Finally, an overview over boosting algorithms and models employed in industry.
https://github.com/dhruvsrikanth/boosting-theory
adaboost binary-classification boosting boosting-algorithms gradient-boosting machine-learning multi-class-classification research-paper weak-learning weak-learning-conditions xgboost
Last synced: 2 months ago
JSON representation
A collection of papers produced on the theory of boosting as applied to binary classification. Further extensions to the multi-class classification problem and necessary and sufficient conditions to ensure boostability i.e. weak learning conditions. Finally, an overview over boosting algorithms and models employed in industry.
- Host: GitHub
- URL: https://github.com/dhruvsrikanth/boosting-theory
- Owner: DhruvSrikanth
- License: mit
- Created: 2022-06-06T21:21:15.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2023-06-28T18:48:15.000Z (almost 3 years ago)
- Last Synced: 2025-10-06T10:54:57.320Z (7 months ago)
- Topics: adaboost, binary-classification, boosting, boosting-algorithms, gradient-boosting, machine-learning, multi-class-classification, research-paper, weak-learning, weak-learning-conditions, xgboost
- Homepage:
- Size: 638 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Boosting and Boostability: Weak Learning Implies Strong Learning
In this paper, we explore the design and analysis of boosting algorithms and the necessary and
sufficient conditions on the weak learners to ensure boostability. Following a literature survey on the
computational learning theory behind boosting, we explore boosting, boostability, and conditions
for both in several boosting algorithms. Finally, we discuss the application of such algorithms in
the binary classification problem and extensions to the multi-class problem.
View the full paper [here](Boosting_and_Boostability.pdf).