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Learning from Good and Bad Data
Philip D. Laird
€ 190.27
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Description for Learning from Good and Bad Data
Hardback. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 212 pages, biography. BIC Classification: UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 240 x 162 x 18. Weight in Grams: 512.
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. ... Read more
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. ... Read more
Product Details
Format
Hardback
Publication date
1988
Publisher
Kluwer Academic Publishers United States
Number of pages
212
Condition
New
Series
The Springer International Series in Engineering and Computer Science
Number of Pages
212
Place of Publication
, United States
ISBN
9780898382631
SKU
V9780898382631
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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