Data Mining Algorithms and Applications

Author: Liang Xun
Publisher:
Publish Date: 2006-04-01
Features: Data mining is a field that involves multiple disciplines such as database technology, computational intelligence, statistics, and pattern recognition. Currently, data mining has been widely applied in various industries. This book comprehensively integrates a large amount of domestic and international new materials and the author's research findings to systematically introduce data mining algorithms, related technologies, and their applications in financial data. After the introduction, the entire book is structurally divided into three parts. The first part specifically introduces the main algorithms of data mining, including decision tree algorithms, neural network algorithms, genetic algorithms, basic statistical analysis methods, Bayesian network algorithms, support vector machine methods, etc. The second part primarily discusses related technologies of data mining, including data warehouse technology, fuzzy processing technology, rough set technology, and target optimization technology. The third part explores some specialized topics in data mining, including internet financial information search engines, internet information flow time series mining, and other issues. The readers of this book can be computer professionals interested in financial applications, or financial professionals interested in computers and the internet. It is suitable for reference by technical personnel in fields such as data mining, machine intelligence, and financial data analysis, as well as university teachers and students.