Contrast Data Mining: Concepts, Algorithms, and Applications (Hardcover)

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life Problems
Contrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and other fields. The book not only presents concepts and techniques for contrast data mining, but also explores the use of contrast mining to solve challenging problems in various scientific, medical, and business domains.

Learn from Real Case Studies of Contrast Mining Applications
In this volume, researchers from around the world specializing in architecture engineering, bioinformatics, computer science, medicine, and systems engineering focus on the mining and use of contrast patterns. They demonstrate many useful and powerful capabilities of a variety of contrast mining techniques and algorithms, including tree-based structures, zero-suppressed binary decision diagrams, data cube representations, and clustering algorithms. They also examine how contrast mining is used in leukemia characterization, discriminative gene transfer and microarray analysis, computational toxicology, spatial and image data classification, voting analysis, heart disease prediction, crime analysis, understanding customer behavior, genetic algorithms, and network security.

《對比數據挖掘：概念、算法和應用》是一本專門收集了數據挖掘領域中分散在文獻中的最新研究成果，使其更容易被數據挖掘和其他領域的研究人員和開發人員所使用。本書不僅介紹了對比數據挖掘的概念和技術，還探討了對比挖掘在科學、醫學和商業領域中解決具有挑戰性問題的應用。

本書中的研究人員來自世界各地，專注於建築工程、生物信息學、計算機科學、醫學和系統工程等領域的對比模式的挖掘和應用。他們展示了各種對比挖掘技術和算法的許多有用和強大的能力，包括基於樹的結構、零壓縮二進制決策圖、數據立方體表示和聚類算法。他們還研究了對比挖掘在白血病特徵描述、區分基因轉移和微陣列分析、計算毒理學、空間和圖像數據分類、投票分析、心臟病預測、犯罪分析、理解客戶行為、遺傳算法和網絡安全等方面的應用。通過真實案例研究，讀者可以從中學習對比挖掘的應用。