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We introduce two dynamic visualization techniques using multi-dimensional scaling to analyze transient data streams such as newswires and remote sensing imagery. While the time-sensitive nature of these data streams requires immediate attention in many applications, the unpredictable and unbounded characteristics of this information can potentially overwhelm many scaling algorithms that require a...
The rapidly expanding market for Spatial Data Mining systems and technologies is driven by pressure from the public sector, environmental agencies and industry to provide innovative solutions to a wide range of different problems. The main objective of the described spatial data mining platform is to provide an open, highly extensible, n-tier system architecture based on the Java 2 Platform, Enterprise...
The Predictive Model Markup Language (PMML) is an XML-based industrial standard for the platform- and system-independent representation of data mining models. It is currently supported by a number of knowledge discovery systems. The primary purpose of the PMML standard is to separate model generation from model storage in order to enable users to view, post-process, and utilize data mining models...
In this chapter, we describe new neural-network techniques developed for visual mining clinical electroencephalograms (EEGs), the weak electrical potentials invoked by brain activity. These techniques exploit the fruitful ideas of Group Method of Data Handling (GMDH). Section 2 briefly describes the standard neural-network techniques that are able to learn well-suited classification modes from data...
Visualization is used in data mining for the visual presentation of already discovered patterns and for discovering new patterns visually. Success in both tasks depends on the ability of presenting abstract patterns as simple visual patterns. Getting simple visualizations for complex abstract patterns is an especially challenging problem. A new approach called inverse visualization (IV) is suggested...
This chapter describes a new technique for extracting patterns and relations visually from multidimensional binary data using monotone Boolean functions. Visual Data Mining has shown benefits in many areas when used with numerical data, but that technique is less beneficial for binary data. This problem is especially challenging in medical applications tracked with binary symptoms. The proposed method...
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