Cost-sensitive decision tree and cost-sensitive naïve Bayes are both new cost-sensitive learning models proposed recently to minimize the total cost of test and misclassifications...
In this paper, a hybrid learning approach named HDT is proposed. HDT simulates human reasoning by using symbolic learning to do qualitative analysis and using neural learning to d...
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...
In this paper, we study the privacy-preserving decision tree building problem on vertically partitioned data. We made two contributions. First, we propose a novel hybrid approach, ...
Therehasbeensurprisinglylittle researchso far that systematicallyinvestigatedthe possibilityof constructinghybrid learningalgorithmsbysimplelocal modificationsto decision tree lea...
Alexander K. Seewald, Johann Petrak, Gerhard Widme...