The major contribution of this paper is the novel KS-Tree algorithm which builds a decision tree in a distributed environment. KS-Tree is applied to some real world data mining problems and compared ...

Bayesian Decision Trees ... a pruning step. This algorithm generates the greedy-modal tree (GMT) which is applicable to both regression and classification problems. We tested the algorithm on various ...

Abstract: every day, we see that a quantitative explosion of digital data has forced ... we encounter the problem of optimizing parallel tasks. So we will propose in this article a method based on the ...

Decision Tree is the simple but powerful classification algorithm of machine learning where a tree or graph-like structure is constructed to display algorithms and reach possible consequences of a ...

The decision tree algorithm falls under the category of supervised learning. They can be used to solve both regression and classification problems. Decision Tree Terminologies ... a threshold to ...