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Data Mining
Data Mining:
A process of analysing business data (often stored in a data warehouse) to uncover hidden trends and patterns and establish relationships. Data mining is normally performed by expert analysts who use specialist software tools.
From: www.oranz.co.uk/glossary_text.htm
The process of using statistical techniques to discover subtle relationships between data items, and the construction of predictive models based on them. The process is not the same as just using an OLAP tool to find exceptional items. Generally, data mining is a very different and more specialist application than OLAP, and uses different tools from different vendors. Normally the users are different, too. OLAP vendors have had little success with their data mining efforts.
From : www.olapreport.com/glossary.htm
Databionic ESOM Tools
Platform : java
License : Open Source, Free
Appears in these categories : Data Mining Data Visualization, Charting
License : Open Source, Free
Appears in these categories : Data Mining Data Visualization, Charting
The Databionic ESOM Tools is a suite of programs to perform data mining tasks like clustering, visualization, and classification with Emergent Self-Organizing Maps (ESOM). Features include:
Training of ESOM with different initialization methods, training algorithms, distance functions, parameter cooling strategies, ESOM grid topologies, and neighborhood kernels.
Visualization of high dimensional dataspace with U-Matrix, P-Matrix, Component Planes, SDH, and more.
Animated visualization of the training process.
Interactive, explorative data analysis and clustering by linking ESOM to the training data, data classifications, and data descriptions.
Creation of ESOM classifier and automated application to new data.
Creation of non-redundant U-Maps from toroid ESOM.
Training of ESOM with different initialization methods, training algorithms, distance functions, parameter cooling strategies, ESOM grid topologies, and neighborhood kernels.
Visualization of high dimensional dataspace with U-Matrix, P-Matrix, Component Planes, SDH, and more.
Animated visualization of the training process.
Interactive, explorative data analysis and clustering by linking ESOM to the training data, data classifications, and data descriptions.
Creation of ESOM classifier and automated application to new data.
Creation of non-redundant U-Maps from toroid ESOM.
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