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KDD
1995
ACM
109views Data Mining» more  KDD 1995»
15 years 10 months ago
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
Michael J. Pazzani
ACL
1993
15 years 8 months ago
Automatic Grammar Induction and Parsing Free Text: A Transformation-Based Approach
In this paper we describe a new technique for parsing free text: a transformational grammar I is automatically learned that is capable of accurately parsing text into binary-branc...
Eric Brill
IJCV
2000
97views more  IJCV 2000»
15 years 6 months ago
Contour Tracking in Clutter: A Subset Approach
A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of c...
Daniel Freedman, Michael S. Brandstein
ICMLA
2010
15 years 4 months ago
An All-at-once Unimodal SVM Approach for Ordinal Classification
Abstract--Support vector machines (SVMs) were initially proposed to solve problems with two classes. Despite the myriad of schemes for multiclassification with SVMs proposed since ...
Joaquim F. Pinto da Costa, Ricardo Sousa, Jaime S....
196
Voted
RSKT
2009
Springer
16 years 1 months ago
Learning Optimal Parameters in Decision-Theoretic Rough Sets
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Joseph P. Herbert, Jingtao Yao