Pattern Recognition Algorithms for Data Mining

Pal, Sankar K., Mitra, Pabitra

  • 出版商: CRC
  • 出版日期: 2019-09-19
  • 售價: $3,310
  • 貴賓價: 9.5$3,145
  • 語言: 英文
  • 頁數: 280
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0367394243
  • ISBN-13: 9780367394240
  • 相關分類: Algorithms-data-structuresData-mining
  • 海外代購書籍(需單獨結帳)

商品描述

Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.

Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

目錄大綱

Introduction. Multiscale data condensation. Unsupervised feature selection. Active learning using support vector machine. Rough-fuzzy case generation. Rough-fuzzy clustering. Rough self-organizing map. Classification, rule generation and evaluation using modular rough-fuzzy MLP. Appendices.