Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work...Lasīt vairāk
Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different...Lasīt vairāk
Gama (artificial intelligence, U. of Porto, Portugal) explores methods of extracting knowledge from data sets that are too large and too dynamic to be squeezed into a conventional database. He introduces the concept and features of data streams then...Lasīt vairāk
The ten algorithms explained in this graduate textbook were presented at the 2006 IEEE International Conference on Data Mining held in Hong Kong. After describing how the algorithm works, each chapter discusses software implementations, provides a co...Lasīt vairāk
Clustering algorithms take data with any number of dimensions and group them into subsets so each member of a subset is near the other members in some sense. In 17 articles including an introduction, contributors describe this phenomenon, focusing on...Lasīt vairāk
For researchers who have complex datasets that garden-variety data-mining techniques do not handle well, Skillicorn explains some of the common matrix decomposition techniques, which break a dataset into its constituent parts in order to analyze it....Lasīt vairāk
