Showing papers on "Dimensionality reduction published in 1976"

On a statistic useful in dimensionality reduction in multivariable linear stochastic system

Abstract: In this paper we study the sampling properties of a test statistic which has important applications in the area of linear stochastic control systems with multi-inputs and multi-outputs. The statistic is the ratio of a partial sum of the eigenvalues of a sample covariance matrix and its trace. It turns out that using a method due to Sugiura we may derive a useful approximation for its distribution up to and including terms of order l/n, where n denotes the appropriate size. Numerical illustrations using real data are given.

AHIMSA: Ad hoc histogram information measure sensing algorithm for feature selection in the context of histogram inspired clustering techniques

Abstract: This letter outlines an approach to the problem of dimensionality reduction in the context of clustering techniques based on multidimensional histogram analysis. The approach is founded on an evaluation of the hills and valleys in the unidimensional histograms along the different features as the basis for assessing the information contained in the individual feature dimensions from the point of view of clusterability of the data set using these features.