We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing fo...
Frank Plastria, Steven De Bruyne, Emilio Carrizosa
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Nearest neighbor (NN) search in high dimensional feature space is widely used for similarity retrieval of multimedia information. However, recent research results in the database ...
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
We investigate the problem of approximate similarity (nearest neighbor) search in high-dimensional metric spaces, and describe how the distance distribution of the query object ca...