Data mining with Clementine

Autor: Colin Shearer, Tom Khabaza
Rok vydání: 1995
Předmět:
Zdroj: IEE Colloquium on Knowledge Discovery in Databases.
Popis: Data mining is the extraction of useful information or knowledge from bodies of data. Data mining is also sometimes referred to as knowledge discovery in databases. Clementine is a comprehensive, integrated toolkit which provides active support for data mining in the form of neural network and rule induction learning techniques, passive support in the form of visualisation, statistical and browsing facilities, and peripheral support for data access and manipulation. Clementine's visual programming interface provides an environment which is easy to use for technological experts and non-experts alike, and provides a convenient organising framework for any data mining technique. Clementine makes machine learning accessible to non-experts. Clementine also goes beyond simple organisational advantages because it reduces the time taken to perform data mining experiments by one to two orders of magnitude. This means that experiments which would previously have been impractical in any realistic project are made possible by Clementine, effectively opening up new areas of exploration. The first commercial version of Clementine is currently on the market and is attracting a great deal of interest. Future versions will extend the machine learning facilities and provide many other new features. The utility of Clementine will continue to grow, and to provide new possibilities for data mining.
Databáze: OpenAIRE