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IJCAI
1993
13 years 7 months ago
Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning
Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This pa...
Usama M. Fayyad, Keki B. Irani
ISCI
2007
130views more  ISCI 2007»
13 years 6 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
ICIP
2005
IEEE
14 years 8 months ago
A classification approach for anatomical regions segmentation
In this paper, a supervised pixel-based classifier approach for segmenting different anatomical regions in abdominal Computed Tomography (CT) studies is presented. The approach co...
Mikhail Kalinin, Daniela Stan Raicu, Jacob D. Furs...
ICML
2005
IEEE
14 years 7 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
COR
2006
97views more  COR 2006»
13 years 6 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