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TSP
2008
173views more  TSP 2008»
13 years 7 months ago
Gaussian Mixture Modeling by Exploiting the Mahalanobis Distance
In this paper, the expectation-maximization (EM) algorithm for Gaussian mixture modeling is improved via three statistical tests. The first test is a multivariate normality criteri...
Dimitrios Ververidis, Constantine Kotropoulos
APPROX
2008
Springer
245views Algorithms» more  APPROX 2008»
13 years 9 months ago
Approximating Optimal Binary Decision Trees
Abstract. We give a (ln n + 1)-approximation for the decision tree (DT) problem. An instance of DT is a set of m binary tests T = (T1, . . . , Tm) and a set of n items X = (X1, . ....
Micah Adler, Brent Heeringa
JDWM
2007
107views more  JDWM 2007»
13 years 7 months ago
Evolutionary Induction of Mixed Decision Trees
This article presents a new evolutionary algorithm (EA) for induction of mixed decision trees. In nonterminal nodes of a mixed tree, different types of tests can be placed, rangin...
Marek Kretowski, Marek Grzes
BIBM
2009
IEEE
164views Bioinformatics» more  BIBM 2009»
14 years 23 days ago
Differential Predictive Modeling for Racial Disparities in Breast Cancer
The primary objective of disparities research is to model the differences across multiple groups and identify the groups that behave significantly different from each other. Indep...
Indranil Palit, Chandan K. Reddy, Kendra L. Schwar...
ML
2000
ACM
185views Machine Learning» more  ML 2000»
13 years 7 months ago
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Tjen-Sien Lim, Wei-Yin Loh, Yu-Shan Shih