Results 211 to 220 of about 77,146 (265)

Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas. [PDF]

open access: yesEntropy (Basel)
Desuó Neto L   +3 more
europepmc   +1 more source

SOME RESULTS IN THE EXTENSION WITH A COHERENT SUSLIN TREE (Aspects of Descriptive Set Theory)

open access: yesSOME RESULTS IN THE EXTENSION WITH A COHERENT SUSLIN TREE (Aspects of Descriptive Set Theory)
openaire  

A Framework for a Decision Tree Learning Algorithm with Rough Set Theory

Communications in Computer and Information Science, 2015
In this paper, we improve the conventional decision tree learning algorithm using rough set theory. First, our approach gets the upper approximate for each class. Next, it generates the decision tree from each upper approximate. Each decision tree shows whether the data item is in this class or not. Our approach classifies the unlabeled data item using
Hamido Fujita, Hakura Jun
exaly   +2 more sources

An Integration of Cloud Transform and Rough Set Theory to Induction of Decision Trees

Fundamenta Informaticae, 2009
Decision trees are one of the most popular data-mining techniques for knowledge discovery. Many approaches for induction of decision trees often deal with the continuous data and missing values in information systems. However, they do not perform well in real situations.
Jing Song, Tianrui Li 0001, Da Ruan 0001
openaire   +1 more source

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