Logo

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Large book cover: The Elements of Statistical Learning: Data Mining, Inference, and Prediction

The Elements of Statistical Learning: Data Mining, Inference, and Prediction
by

Publisher: Springer
ISBN/ASIN: 0387848576
ISBN-13: 9780387848570
Number of pages: 764

Description:
This book is an attempt to bring together many of the important new ideas in learning, and explain them in a statistical framework. While some mathematical details are needed, the authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties. This book will appeal not just to statisticians but also to researchers and practitioners in a wide variety of fields.

Home page url

Download or read it online for free here:
Download link
(8.2MB, PDF)

Similar books

Book cover: Inductive Logic Programming: Theory and MethodsInductive Logic Programming: Theory and Methods
by - ScienceDirect
Inductive Logic Programming is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge. The authors survey the most important theories and methods of this new field.
(18687 views)
Book cover: Reinforcement Learning: An IntroductionReinforcement Learning: An Introduction
by - The MIT Press
The book provides a clear and simple account of the key ideas and algorithms of reinforcement learning. It covers the history and the most recent developments and applications. The only necessary mathematical background are concepts of probability.
(10746 views)
Book cover: Optimal and Learning Control for Autonomous RobotsOptimal and Learning Control for Autonomous Robots
by - arXiv.org
The starting point is the formulation of of an optimal control problem and deriving the different types of solutions and algorithms from there. These lecture notes aim at supporting this unified view with a unified notation wherever possible.
(315 views)
Book cover: Algorithms for Reinforcement LearningAlgorithms for Reinforcement Learning
by - Morgan and Claypool Publishers
We focus on those algorithms of reinforcement learning that build on the theory of dynamic programming. We give a comprehensive catalog of learning problems, describe the core ideas, followed by the discussion of their properties and limitations.
(1636 views)