Data Mining Techniques and Applications: An Introduction
Du, Hongbo
Data Mining Techniques and Applications: An Introduction - Delhi Cengage Learning India Private Limited 2010 - 315
This concise and approachable introduction to data mining s a mixture of data mining techniques originating from statistics, machine learning and databases and presents them in an algorithmic approach. Aimed primarily at undergraduate readers, it presents not only the fundamental principles and concepts of the subject in an easy-to-understand way, but also hands on, practical instruction on data mining techniques, that readers can put into practice as they go along using the freely downloadable Weka toolkit. Author Hongbo Du shares his years of commercial, as well as research-based, experience in the field through extensive examples and real-world case studies, highlighting how data mining solutions provided by software tools are used in practical problem solving. Covering not only traditional areas of data mining such as association, clustering and classification, this text also explains topics such as data warehousing, online-analytic processing and text mining.
9788131519554
Computational intelligence
machine learning
Data mining
Engineering mathematics
Management information systems
006.312 DU
Data Mining Techniques and Applications: An Introduction - Delhi Cengage Learning India Private Limited 2010 - 315
This concise and approachable introduction to data mining s a mixture of data mining techniques originating from statistics, machine learning and databases and presents them in an algorithmic approach. Aimed primarily at undergraduate readers, it presents not only the fundamental principles and concepts of the subject in an easy-to-understand way, but also hands on, practical instruction on data mining techniques, that readers can put into practice as they go along using the freely downloadable Weka toolkit. Author Hongbo Du shares his years of commercial, as well as research-based, experience in the field through extensive examples and real-world case studies, highlighting how data mining solutions provided by software tools are used in practical problem solving. Covering not only traditional areas of data mining such as association, clustering and classification, this text also explains topics such as data warehousing, online-analytic processing and text mining.
9788131519554
Computational intelligence
machine learning
Data mining
Engineering mathematics
Management information systems
006.312 DU
