multivariate statistical techniques such as cluster analysis, multidimensional scaling and principal component analysis were applied to evaluate the temporal and spatial variations in water quality data set generated for two years (2008-2010) from six monitoring stations of veli-akkulam lake and compared with a regional reference lake vellayani of south india. seasonal variations of 14 differen...

Visualization techniques are especially relevant to multidimensional data, the analysis of which is limited by human perception abilities. The paper presents a hybrid method of multidimensional data analysis. The main goal was to test the efficiency of the method in the context of real-life medical data. A short survey of issues and techniques concerned with data visualization are also included.

The purpose of OLAP (On-Line Analytical Processing) systems is to provide a framework for the analysis of multidimensional data. Many tasks related to analysing multidimensional data and making business decisions are still carried out manually by analysts (e.g. financial analysts, accountants, or business managers). An important and common task in multidimensional analysis is business diagnosis...

Visualization techniques are especially relevant to multidimensional data, the analysis of which is limited by human perception abilities. The paper presents a hybrid method of multidimensional data analysis. The main goal was to test the efficiency of the method in the context of real-life medical data. A short survey of issues and techniques concerned with data visualization are also included.

Functional data analysis (FDA) deals with samples where a whole function is observed for each individual. A particular case is when the observed functions are densities, that is also an example of infinite dimensional compositional data. We focus on the dimensionality reduction problem for this particular type of data. Several methods are considered here: functional principal components analysi...

In this paper we consider how multidimensional clustering can be complemented by interactive visualization. We propose a link between geovisualization and data mining systems for supporting an iterative analysis cycle, including data pre-processing and visual exploration, automatic detection of clusters in multidimensional space of user-selected attributes, and visual analysis of cluster analys...