Data complexity assessment in undersampled classification of high-dimensional biomedical data
β Scribed by R. Baumgartner; R.L. Somorjai
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 383 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0167-8655
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## Abstract In this work, a family of generative Gaussian models designed for the supervised classification of highβdimensional data is presented as well as the associated classification method called HighβDimensional Discriminant Analysis (HDDA). The features of these Gaussian models are as follow
Our ability to record increasingly larger and more complex sets of data is accompanied by a decline in our capacity to interpret and understand these data in the fullest sense. Multivariate analysis partially assists us in our quest by reducing the dimensionality in optimal ways, but our view is stu