Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
Classification is one of the key issues in the fields of decision sciences and knowledge discovery. This paper presents a new approach for constructing a classifier, based on an e...
Guoqing Chen, Hongyan Liu, Lan Yu, Qiang Wei, Xing...
Attempts to extract logical rules from data often lead to large sets of classification rules that need to be pruned. Training two classifiers, the C4.5 decision tree and the Non-Ne...
Karol Grudzinski, Marek Grochowski, Wlodzislaw Duc...