Understanding and using Rough Set based Feature Selection
โ Scribed by Muhammad Summair Raza, Usman Qamar
- Publisher
- Springer
- Year
- 2017
- Tongue
- English
- Leaves
- 194
- Category
- Library
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
<p><p>This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent
The rough and fuzzy set approaches presented here open up many new frontiers for continued research and development. Computational Intelligence and Feature Selection provides readers with the background and fundamental ideas behind Feature Selection (FS), with an emphasis on techniques based on rou
Computational Intelligence and Feature Selection provides readers with the background and fundamental ideas behind Feature Selection (FS), with an emphasis on techniques based on rough and fuzzy sets. For readers who are less familiar with the subject, the book begins with an introduction to fuzzy s
<p>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 m
<p><p>Rough Set Theory, introduced by Pawlak in the early 1980s, has become an important part of soft computing within the last 25 years. However, much of the focus has been on the theoretical understanding of Rough Sets, with a survey of Rough Sets and their applications within business and industr