The amount of data collected in the last decades has become a source of valuable information, allowing organizations to improve their competitiveness. However, the associated data...
Humberto Luiz Razente, Fabio Jun Takada Chino, Mar...
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...