Rough Set Based Classification Systems is popular PDF and ePub book, written by Robert K. Nowicki in 2018-12-17, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Rough Set Based Classification Systems can be Read Online from any device for your convenience.

Rough Set Based Classification Systems Book PDF Summary

This book demonstrates an original concept for implementing the rough set theory in the construction of decision-making systems. It addresses three types of decisions, including those in which the information or input data is insufficient. Though decision-making and classification in cases with missing or inaccurate data is a common task, classical decision-making systems are not naturally adapted to it. One solution is to apply the rough set theory proposed by Prof. Pawlak. The proposed classifiers are applied and tested in two configurations: The first is an iterative mode in which a single classification system requests completion of the input data until an unequivocal decision (classification) is obtained. It allows us to start classification processes using very limited input data and supplementing it only as needed, which limits the cost of obtaining data. The second configuration is an ensemble mode in which several rough set-based classification systems achieve the unequivocal decision collectively, even though the systems cannot separately deliver such results.

Detail Book of Rough Set Based Classification Systems PDF

Rough Set   Based Classification Systems
  • Author : Robert K. Nowicki
  • Release : 17 December 2018
  • Publisher : Springer
  • ISBN : 9783030038953
  • Genre : Technology & Engineering
  • Total Page : 188 pages
  • Language : English
  • PDF File Size : 7,5 Mb

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