Tasuta kohaletoimetamine tellimustele üle 29 €
  • check 10+ miljonit raamatut
  • check Uued tooted iga päev
  • check Meid usaldab üle 1 miljoni kliendi
  • check Hea hind ja allahindlused
  • check Tarne üle kogu Euroopa

Learning from Good and Bad Data - Philip D. Laird

inglise keel
2011-10-05
152,45 € 254,08 €

-40% koodiga BOOKS

Meie tarnija laos

Saadetis 12-18 tööpäeva jooksul

30-päevane tagastamisõigus

This monograph is a contribution to the study of the identification problem: the problem of identifying an item from a known class us­ ing positive and negative examples. This problem is considered to be an important component of the process of inductive learning, and as such has been studied extensively. In the overview we shall explain the objectives of this work and its place in the overall fabric of lea ... Täielik kirjeldus

Võib-olla meeldib sulle ka

Kirjeldus

This monograph is a contribution to the study of the identification problem: the problem of identifying an item from a known class us­ ing positive and negative examples. This problem is considered to be an important component of the process of inductive learning, and as such has been studied extensively. In the overview we shall explain the objectives of this work and its place in the overall fabric of learning research. Context. Learning occurs in many forms; the only form we are treat­ ing here is inductive learning, roughly characterized as the process of forming general concepts from specific examples. Computer Science has found three basic approaches to this problem: ¿ Select a specific learning task, possibly part of a larger task, and construct a computer program to solve that task . ¿ Study cognitive models of learning in humans and extrapolate from them general principles to explain learning behavior. Then construct machine programs to test and illustrate these models. xi Xll PREFACE ¿ Formulate a mathematical theory to capture key features of the induction process. This work belongs to the third category. The various studies of learning utilize training examples (data) in different ways. The three principal ones are: ¿ Similarity-based (or empirical) learning, in which a collection of examples is used to select an explanation from a class of possible rules.

Lisateave

Autor Philip D. Laird
Kirjastaja Springer New York
Series The Springer International Series in Engineering and Computer Science
Väljalaskeaasta 2011
Kaanetüüp Pehme kaanega
EAN 9781461289517
Kirjuta oma arvustus
Te vaatate: Learning from Good and Bad Data
Teie hinnang:

Goodreads'i arvustused

152,45 € 254,08 €