Abstract. In the paper, a new method of decision tree learning for costsensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed...
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
Random decision tree is an ensemble of decision trees. The feature at any node of a tree in the ensemble is chosen randomly from remaining features. A chosen discrete feature on a...
– This paper presents a method for designing classifier to automate an evaluation process of protein crystallization growth states. The classifier is designed by binary decision ...
A common form of prior knowledge in economic modelling concerns the monotonicity of relations between the dependent and explanatory variables. Monotonicity may also be an important...