Logo

Boosting: Foundations and Algorithms

Large book cover: Boosting: Foundations and Algorithms

Boosting: Foundations and Algorithms
by

Publisher: The MIT Press
ISBN-13: 9780262310413
Number of pages: 544

Description:
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate 'rules of thumb'. A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry.

Home page url

Download or read it online for free here:
Read online
(online html)

Similar books

Book cover: An Introductory Study on Time Series Modeling and ForecastingAn Introductory Study on Time Series Modeling and Forecasting
by - arXiv
This work presents a concise description of some popular time series forecasting models used in practice, with their features. We describe three important classes of time series models, viz. the stochastic, neural networks and SVM based models.
(12639 views)
Book cover: Introduction to Machine LearningIntroduction to Machine Learning
by - Cambridge University Press
Over the past two decades Machine Learning has become one of the mainstays of information technology and a rather central part of our life. Smart data analysis will become even more pervasive as a necessary ingredient for technological progress.
(10409 views)
Book cover: The Elements of Statistical Learning: Data Mining, Inference, and PredictionThe Elements of Statistical Learning: Data Mining, Inference, and Prediction
by - Springer
This book brings together many of the important new ideas in learning, and explains them in a statistical framework. The authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties.
(41547 views)
Book cover: Reinforcement LearningReinforcement Learning
by - InTech
This book describes and extends the scope of reinforcement learning. It also shows that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional controllers.
(22160 views)