… Are we sure that the advantages of decision trees do not … algorithms, which employ decision
trees as the cornerstone of … effectiveness of decision trees also in a parallel environment. …

… Decision tree classifier, and the Anomaly intrusion detection system … decision tree c5 and
one class SVM classifier, were chosen to build the intrusion detection system. The decision tree …

… This paper explores the capabilities of decision tree ensembles (DTEs) for detecting and …
The SHM methodology herein discussed, denoted as D 2 -DTE, is based on decision trees …

… Finally, the implementation of the patient classification model with decision tree into machine
… decision tree method make it easier for patients and hospitals to classify children's nutrition. …

… The decision tree, known for its speed and userfriendliness, is … an effective decision
tree-based detection framework. … in NIDS design and various decision tree techniques, research …

… The Decision Tree algorithm testing in this study using RapidMiner tools produced an
accuracy of 82.91% (See Table 6). The computational time of this algorithm is about 13 seconds. …

… Suppose we wish to prove that two decision trees represent the same function; we … decision
trees. In what follows, we take an approach that enriches the language of decision trees with …

… reconstruction algorithm for decision trees: given query access to a function f that is close to
a small decision tree, this algorithm provides fast query access to a small decision tree that is …

… , four decision tree algorithms corresponding to C5.0, classification and regression trees (…
(CHAID), and quick unbiased efficient statistical tree (QUEST) were applied to elemental …

… The focus of the paper is the pruning feature of the decision tree classification algorithm. In
addition to the discussion of different kinds of pruning, there performance and accuracy tests …