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{ "item_title" : "Lazy Learning", "item_author" : [" David W. AHA "], "item_description" : "This edited collection describes recent progress on lazy learning, a branch of machine learning concerning algorithms that defer the processing of their inputs, reply to information requests by combining stored data, and typically discard constructed replies. It is the first edited volume in AI on this topic, whose many synonyms includeinstance-based',memory-based'.exemplar-based', andlocal learning', and whose topic intersects case-based reasoning and edited k-nearest neighbor classifiers. It is intended for AI researchers and students interested in pursuing recent progress in this branch of machine learning, but, due to the breadth of its contributions, it should also interest researchers and practitioners of data mining, case-based reasoning, statistics, and pattern recognition.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/0/79/234/584/0792345843_b.jpg", "price_data" : { "retail_price" : "169.99", "online_price" : "169.99", "our_price" : "169.99", "club_price" : "169.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Lazy Learning|David W. AHA

Lazy Learning

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Overview

This edited collection describes recent progress on lazy learning, a branch of machine learning concerning algorithms that defer the processing of their inputs, reply to information requests by combining stored data, and typically discard constructed replies. It is the first edited volume in AI on this topic, whose many synonyms include instance-based', memory-based'. exemplar-based', and local learning', and whose topic intersects case-based reasoning and edited k-nearest neighbor classifiers. It is intended for AI researchers and students interested in pursuing recent progress in this branch of machine learning, but, due to the breadth of its contributions, it should also interest researchers and practitioners of data mining, case-based reasoning, statistics, and pattern recognition.

This item is Non-Returnable

Details

  • ISBN-13: 9780792345848
  • ISBN-10: 0792345843
  • Publisher: Springer
  • Publish Date: May 1997
  • Dimensions: 9.21 x 6.14 x 0.94 inches
  • Shipping Weight: 1.71 pounds
  • Page Count: 424

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