Projecting multidimensional data to a lower-dimensional visual display as a scatter-plot-like visualization is a common approach for analyzing multidimensional data. Many dimension reduction techniques exist for performing ...

Dimensionality reduction algorithms may be of great help as decision support, representing the information as a map which summarizes the data similarities. When data come with an assigned class label, such a map can be ...

The analysis of the big volumes of data requires efficient and robust dimension reduction techniques to represent data into lower-dimensional spaces, which ease human understanding. This paper presents a study of the ...

This work describes a novel interactive visual clustering system. It combines a 2D projection with a clustering algorithm that operates on this projected data. Example-based interactions are supported directly through the ...

Dealing with high-dimensional data becomes very common nowadays; visualization is a natural preprocessing to have an overview of such data. A lot of dimensionality reduction methods exist; many of them require to tune a ...

As dimensionality increases, analysts are faced with difficult problems to make sense of their data. In exploratory data analysis, multidimensional scaling projections can help analyst to discover patterns by identifying ...