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» An Empirical Evaluation of Supervised Learning for ROC Area
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KDD
2006
ACM
180views Data Mining» more  KDD 2006»
15 years 9 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
ICML
2003
IEEE
15 years 2 months ago
An Evaluation on Feature Selection for Text Clustering
Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this...
Tao Liu, Shengping Liu, Zheng Chen, Wei-Ying Ma
IJIT
2004
14 years 10 months ago
Computing Entropy for Ortholog Detection
Abstract-- Biological sequences from different species are called orthologs if they evolved from a sequence of a common ancestor species and they have the same biological function....
Hsing-Kuo Pao, John Case
111
Voted

Publication
400views
14 years 4 months ago
Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting
For quantitative analysis of histopathological images, such as the lymphoma grading systems, quantification of features is usually carried out on single cells before categorizing...
Hui Kong, Metin Gurcan, and Kamel Belkacem-Boussai...
COR
2006
97views more  COR 2006»
14 years 9 months ago
Evaluating the performance of cost-based discretization versus entropy- and error-based discretization
Discretization is defined as the process that divides continuous numeric values into intervals of discrete categorical values. In this article, the concept of cost-based discretiz...
Davy Janssens, Tom Brijs, Koen Vanhoof, Geert Wets