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{ "item_title" : "Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems", "item_author" : [" Xenia Naidenova", "Dmitry I. Ignatov "], "item_description" : "The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users' requirements and the quality of solving targeted problems in domain applications. Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and compares the most effective algorithms for mining all kinds of logical rules. Global academics and professionals in related fields have come together to create this unique knowledge-sharing resources which will serve as a forum for future collaborations.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/46/661/900/1466619007_b.jpg", "price_data" : { "retail_price" : "195.00", "online_price" : "195.00", "our_price" : "195.00", "club_price" : "195.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems|Xenia Naidenova

Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems

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Overview

The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users' requirements and the quality of solving targeted problems in domain applications. Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and compares the most effective algorithms for mining all kinds of logical rules. Global academics and professionals in related fields have come together to create this unique knowledge-sharing resources which will serve as a forum for future collaborations.

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Details

  • ISBN-13: 9781466619005
  • ISBN-10: 1466619007
  • Publisher: Igi Global Scientific Publishing
  • Publish Date: July 2012
  • Dimensions: 11 x 8.5 x 0.75 inches
  • Shipping Weight: 2.31 pounds
  • Page Count: 330

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