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IPL
1998
95views more  IPL 1998»
13 years 8 months ago
A Variation on the Zero-One Law
Given a decision problem P and a probability distribution over binary strings, for each n, draw independently an instance xn of P of length n. What is the probability that there i...
Andreas Blass, Yuri Gurevich, Vladik Kreinovich, L...
ISBI
2004
IEEE
14 years 9 months ago
Performance-Based Multi-Classifier Decision Fusion for Atlas-Based Segmentation of Biomedical Images
Combinations of multiple classifiers have been found to be consistently more accurate than a single classifier. The construction of multiple independent classifiers, however, is t...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
CAIP
2009
Springer
114views Image Analysis» more  CAIP 2009»
14 years 9 days ago
Decision Trees Using the Minimum Entropy-of-Error Principle
Binary decision trees based on univariate splits have traditionally employed so-called impurity functions as a means of searching for the best node splits. Such functions use estim...
Joaquim Marques de Sá, João Gama, Ra...
IDEAL
2000
Springer
14 years 17 days ago
Quantization of Continuous Input Variables for Binary Classification
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
Michal Skubacz, Jaakko Hollmén
TIT
2002
125views more  TIT 2002»
13 years 8 months ago
Optimal bi-level quantization of i.i.d. sensor observations for binary hypothesis testing
We consider the problem of binary hypothesis testing using binary decisions from independent and identically distributed (i.i.d). sensors. Identical likelihood-ratio quantizers wit...
Qian Zhang, Pramod K. Varshney, Richard D. Wesel