VISRED - Numerical Data Mining with Linear and Nonlinear Techniques

Authors

Abstract

Numerical data mining is a task for which several techniques have been developed that can provide a quick insight into a practical problem, if an easy to use common software platform is available. VISRED- Data Visualisation by Space Reduction presented here, aims to be such a tool for data classification and clustering. It allows the quick application of Principal Component Analysis, Nonlinear Principal Component Analysis, Multidimensional Scaling (classical and non classical). For clustering several techniques have been included: hierarchical, k-means, subtractive, fuzzy k-means, SOM- Self Organizing Map (batch and recursive versions). It reads from and writes to Excel sheets. Its utility is shown with two applications: the visbreaker process part of an oil refinery and the UCI benchmark problem of breast cancer diagnosis.

Subject

classification; data mining ; diagnosis

Related Project

CLASSE - Classificação Sintética para Supervisão Industrial (Synthetic Classification for Industrial Supervision)

Conference

Industrial Conference on Data Mining 2007, July 2007