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IJCAI
1997
13 years 7 months ago
Minimum Splits Based Discretization for Continuous Features
Discretization refers to splitting the range of continuous values into intervals so as to provide useful information about classes. This is usually done by minimizing a goodness m...
Ke Wang, Han Chong Goh
EVOW
2010
Springer
14 years 1 months ago
Top-Down Induction of Phylogenetic Trees
We propose a novel distance based method for phylogenetic tree reconstruction. Our method is based on a conceptual clustering method that extends the well-known decision tree learn...
Celine Vens, Eduardo Costa, Hendrik Blockeel
TSP
2008
173views more  TSP 2008»
13 years 6 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
ECML
2007
Springer
14 years 10 days ago
Decision Tree Instability and Active Learning
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable – they can produce drastic...
Kenneth Dwyer, Robert Holte
CSDA
2008
128views more  CSDA 2008»
13 years 6 months ago
Classification tree analysis using TARGET
Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
J. Brian Gray, Guangzhe Fan