Statistical Learning Theory by Vladimir N.Vapnik eBook Free Download

 

Statistical Learning Theory by Vladimir N.Vapnik eBook Free Download

Statistical Learning Theory by Vladimir N.Vapnik eBook Free Download

Statistical Learning Theory by Vladimir N.Vapnik eBook Free Download

Introduction:

This book is dedicated to factual learning hypothesis, the hypothesis that investigates methods for evaluating practical reliance from a given accumulation of information. This issue is extremely broad. It covers critical subjects of traditional statisticsin specific, discriminant investigation, relapse examination, and the thickness estimation issue.

In this book we consider another worldview for taking care of these issues: the purported learning worldview that was created in the course of the most recent 30 years. In differentiation to the traditional insights produced for extensive specimens and in view of utilizing different sorts of from the earlier data, the new hypothesis was produced for little information tests and does not depend on from the earlier learning around a issue to be settled. Rather it considers a structure on the arrangement of capacities executed by the learning machine (an arrangement of settled subsets of capacities) where a particular measure of subset limit is characterized. To control the speculation in the system of this worldview, one has to consider two components, to be specific, the nature of guess of given information by the picked capacity and the limit of the subset of capacities from which the approximating capacity was picked. This book displays a complete investigation of this kind of induction (learning process). It contains:

  • The general subjective hypothesis that incorporates the fundamental and adequate conditions for consistency of learning procedures
  • The general quantitative hypothesis that incorporates limits on the rate of meeting (the rate of speculation) of these learning forms
  • Principles for evaluating capacities from a little gathering of information that depend on the created hypothesisMethods of capacity estimation and their application to comprehending genuine living issues that depend on these standards

The book has three sections: “Hypothesis of Learning and Generalization,” “Bolster Vector Estimation of Functions,” and “Measurable Foundation of Learning Theory.” The principal part, “Hypothesis of Learning and Generalization,” investigates v.

Contents:

  1. Ttl. Issue ot Induction and Statistical Induction 1
  2. Two Approache. to the learning Problem 19
  3. Routines for Solvlnv m-PolHtd Problems 51
  4. EstlmaUon of ttle Probability Measure and Problem of leeming 59
  5. Condilionsior Consistency ot Empirical Risk
  6. Minimization PrInciple 79
  7. Limits on the Risk tOJ Indicator misfortune FuncUons 121
  8. low., Bounds on th. Hazard ot the ERM Princlpl. 169
  9. Limits on 1M Risk tor Real-Volued Lou Functions 183
  10. The SINelural Risk Mlnlmlzollon Principle 219
  11. stochasflc 1I1-PoMd Problem, 293

Statistical Learning Theory by Vladimir N.Vapnik eBook Free Download

 

Statistical Learning Theory by Vladimir N.Vapnik eBook Free Download

 

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