| Three Approaches to Data Analysis: Test Theory, Rough Sets and Logical Analysis of Data 2013 Edition Contributor(s): Chikalov, Igor (Author), Lozin, Vadim (Author), Lozina, Irina (Author) |
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ISBN: 3642445985 ISBN-13: 9783642445989 Publisher: Springer OUR PRICE: $104.49 Product Type: Paperback - Other Formats Published: August 2014 |
| Additional Information |
| BISAC Categories: - Computers | Intelligence (ai) & Semantics - Technology & Engineering | Engineering (general) |
| Dewey: 006.3 |
| Series: Intelligent Systems Reference Library |
| Physical Information: 0.47" H x 6.14" W x 9.21" (0.70 lbs) 202 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958, - Rough Sets, founded by Zdzislaw I. Pawlak (1926-2006); the first publications appeared in 1981 and 1982, - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. |
