Description: A simple method of data classification using rough set theory is described, as implemented by the tools in Alexander Ohra s software application ROSETTA Platform: |
Size: 412672 |
Author:saomaket |
Hits:
Description: 本书详尽地阐述了数据挖掘与知识发现领域中的一些基本理论和研究方法。介绍了KDD与数据挖掘的概念数据挖掘对象知识发现过程研究方法以及相关研究领域和应用范围。作为知识发现的数据预处理工作，简要叙述了数据清理、数据约简、数据概念等级分层、多维数据模型等内容。书中较详细地介绍了粗糙集、模糊集、聚类分析、关联规则、人工神经网络、分类与预测等数据挖掘方法，最后还简要介绍了多媒体数据挖掘工作的有关进展。 本书可以作为计算机科学与技术专业和信息科学方向高年级本科生和研究生的教材或参考书，也可供有关科技人员学习参考。
-The book detailed description of data mining and knowledge discovery in the field of some of the basic theory and research method. Introduces the concept of data mining KDD and data mining knowledge discovery process research methods and related research areas and applications. As a knowledge discovery data preprocessing, briefly describes the data cleaning, data reduction, data concept hierarchy, multidimensional data model etc.. The book describes in detail the rough set, fuzzy set, association rule, cluster analysis, artificial neural network, classification and prediction method of data mining, and also briefly introduces the multimedia data mining related work in progress. This book can serve as a professional computer science and technology and information science graduate and advanced undergraduate textbooks or reference books, is also available for study and reference about scientific and technical personnel. Platform: |
Size: 1608704 |
Author:冯荣俊 |
Hits:
Description: we peresent full pakage of the methods that apply rough set theory in the
context of segmentation (or partitioning) of multichannel medical imaging
data. We put this approach into a semi-automatic framework, where
the user specifies the classes in the data by selecting respective regions in
2D slices. Rough set theory provides means to compute lower and upper
approximation of the classes. The boundary region between the lower
and the upper approximations represents the uncertainty of the classification.
We present an approach to automatically compute segmentation
rules the rough set classification using a k-means approach.-we peresent full pakage of the methods that apply rough set theory in the
context of segmentation (or partitioning) of multichannel medical imaging
data. We put this approach into a semi-automatic framework, where
the user specifies the classes in the data by selecting respective regions in
2D slices. Rough set theory provides means to compute lower and upper
approximation of the classes. The boundary region between the lower
and the upper approximations represents the uncertainty of the classification.
We present an approach to automatically compute segmentation
rules the rough set classification using a k-means approach. Platform: |
Size: 15299584 |
Author:Mohamed A. El-Sayed |
Hits:
Search - rough set theory classification