Please use this identifier to cite or link to this item:
|Title:||VPMCD: Variable interaction modeling approach for class discrimination in biological systems|
|Authors:||Raghuraj, R. |
Variable predictive models
|Source:||Raghuraj, R., Lakshminarayanan, S. (2007-03-06). VPMCD: Variable interaction modeling approach for class discrimination in biological systems. FEBS Letters 581 (5) : 826-830. ScholarBank@NUS Repository. https://doi.org/10.1016/j.febslet.2007.01.052|
|Abstract:||Data classification algorithms applied for class prediction in computational biology literature are data specific and have shown varying degrees of performance. Different classes cannot be distinguished solely based on interclass distances or decision boundaries. We propose that inter-relations among the features be exploited for separating observations into specific classes. A new variable predictive model based class discrimination (VPMCD) method is described here. Three well established and proven data sets of varying statistical and biological significance are utilized as benchmark. The performance of the new method is compared with advanced classification algorithms. The new method performs better during different tests and shows higher stability and robustness. The VPMCD is observed to be a potentially strong classification approach and can be effectively extended to other data mining applications involving biological systems. © 2007 Federation of European Biochemical Societies.|
|Source Title:||FEBS Letters|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 6, 2017
WEB OF SCIENCETM
checked on Nov 22, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.