… decision trees and trees designed for machine learning. The unfolding and progressive
elucidation of the various features of trees … in exceptionally adaptable decision tree tools, …

… In practice, boosting is often applied to combine decision trees. Alternating decision trees
11 are a generalization of decision trees that result from applying a variant of boosting to …

… Decision Trees are considered to be one of the most popular … decision tree from available
data. This paper presents an updated survey of current methods for constructing decision tree …

… a decision has to be made for an unsolved case, we start with the root node of the decision
tree … the attribute values in the decision tree until the leaf node is reached representing the …

… Abstract Decision tree … decision tree issues and current research points. Of course, a single
article cannot be a complete review of all algorithms (also known induction classification trees…

… 1decision tree,2 which has tremendous potential as a decision-making tool. The decision tree
can … We shall be hearing a great deal about decision trees in the years ahead. Although a …

… If the value was below this threshold we would continue with the decision tree commencing
with T4U measured = t, while a value above this threshold would lead us to the decision tree …

… This paper summarizes an approach to synthesizing decision trees that has been used in
a variety of systems, and it describes one such system, ID3, in detail. Results from recent …

… Techniques that represent knowledge about classification tasks in the form of decision trees
… of the decision tree and for each outcome 0, we build a subsidiary decision tree by invoking …

… A decision tree or diagram is a model of the evaluation of a … Decision trees find many
applications in decision table … Owing to this broad applicability, results about decision trees are …