Consistency of Learning Processes

  • Vladimir N. Vapnik
Chapter
Part of the Statistics for Engineering and Information Science book series (ISS)

Abstract

The goal of this part of the theory is to describe the conceptual model for learning processes that are based on the empirical risk minimization inductive principle. This part of the theory has to explain when a learning machine that minimizes empirical risk can achieve a small value of actual risk (can generalize) and when it cannot. In other words, the goal of this part is to describe necessary and sufficient conditions for the consistency of learning processes that minimize the empirical risk.

Keywords

Probability Measure Indicator Function Uniform Convergence Elementary Event Inductive Inference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Vladimir N. Vapnik
    • 1
  1. 1.Room 3-130AT&T Labs-ResearchRed BankUSA

Personalised recommendations