- We will send in 10–14 business days.
/images/books/13365146/9783790825084.jpg)
- Publisher: Physica Verlag
- Year: 2010
- Pages: 537
- ISBN-10: 3790825085
- ISBN-13: 9783790825084
- Format: 15.6 x 23.4 x 2.8 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Data Mining, Rough Sets and Granular Computing (e-book) (used book) | bookbook.eu
Reviews
Description
During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par- ticularly true in the realm of e-commerce, where data mining is moving from a nice-to-have to a must-have status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw- ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 22d.23:42:54
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Publisher: Physica Verlag
- Year: 2010
- Pages: 537
- ISBN-10: 3790825085
- ISBN-13: 9783790825084
- Format: 15.6 x 23.4 x 2.8 cm, minkšti viršeliai
- Language: English English
During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par- ticularly true in the realm of e-commerce, where data mining is moving from a nice-to-have to a must-have status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw- ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing.
Reviews