Decision trees are among the most effective and interpretable classification algorithms while ensembles techniques have been proven to alleviate problems regarding over-fitting and...
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...
While decision trees have been used primarily for classification, they can also model regression or function approximation. Like classification trees, regression trees often yield...
Abstract. In some learning settings, the cost of acquiring features for classification must be paid up front, before the classifier is evaluated. In this paper, we introduce the fo...
Jason V. Davis, Jungwoo Ha, Christopher J. Rossbac...
The main focus of image mining in the proposed method is concerned with the classification of brain tumor in the CT scan brain images. The major steps involved in the system are: p...