For an adequate analysis of pathological speech signals, a sizeable number of parameters is required, such as those related to jitter, shimmer and noise content. Often this kind of high-dimensional signal representation ...

With the advent of interactive techniques for multidimensional data visualization using dimensionality reduction, new possibilities of dealing with data complexity were introduced. The idea behind those methods is to allow ...

In this paper, a methodological data condensation approach for reducing tabular big datasets in classification problems is presented, named FDR2-BD. The key of our proposal is to analyze data in a dual way (vertical and ...

Dimensionality Reduction is a commonly used method to reduce the number of dimensions of data. In this work, we verified its influence in classification process using combinations of projection techniques as dimensionality ...

High Angular Resolution Diffusion Imaging (HARDI) is a type of brain imaging that collects a very large amount of data, and if many subjects are considered then it amounts to a big data framework (e.g., the human connectome ...

A summary table is a tabular representation of summary data, and is a useful data structure for statistical databases. Primitive summary tables are basic building blocks of summary tables, and can be represented as relations ...