The inductive learning methodology known as decision trees, concerns the ability to classify objects based on their attributes values, using a tree like structure from which decision rules can be accrued. In this article, a description of decision trees is given, with the main emphasis on their operation in a fuzzy environment. A first reference to decision trees is made in Hunt et al. (1966), ...

INTRODUCTION It is well known that the performance of most data mining algorithms can be deteriorated by features that do not add any value to learning tasks. Feature selection can be used to limit the effects of such features by seeking only the relevant subset from the original features (de Souza et al., 2006). This subset of the relevant features is discovered by removing those that are cons...

We describe several improvements to Freund and Schapire's AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each of their predictions. We give a simplified analysis of AdaBoost in this setting, and we show how this analysis can be used to find improved parameter settings as well as a refined criterion for training weak hypotheses. We give a spe...

Breast cancer represents the second important cause of cancer deaths in women today and it is the most common type of cancer in women. Disease diagnosis is one of the applications where data mining tools are proving successful results. Data mining with decision trees is popular and effective data mining classification approach. Decision trees have the ability to generate understandable classifi...

There are two approaches in the top-down construction of rst order decision trees that use de nite or normal clauses. The covering approach [5, 3] builds one clause at a time that covers part of positive examples, and repeats this process until no positive examples remain uncovered. The divide-and-conquer approach [1, 2] on the other hand divides the given examples into smaller subsets recursiv...

Perfectionism has previously been identified as having a significant negative impact on therapeutic outcome at termination in the brief (16-week) treatment of depression (S. J. Blatt, D. M. Quinlan, P. A. Pilkonis, & T. Shea, 1995) as measured by the 5 primary outcome measures used in the National Institute of Mental Health Treatment of Depression Collaborative Research Program (TDCRP). The pre...

Changes in the permanent upper central incisors (Hutchinsonian teeth) and in the permanent first molars (Moon, 1877, 1884; Pfluger, 1924) are two of the most important stigmata of late congenital syphilis. These stigmata are not seen until the second dentition, in the incisors after about 7 years of age and in the molars after the 6th year. In radiographs however, Stokes and Gardner (1923) demo...

Karen Ann Quinlan and Theresa Marie Schiavo are names tied to legal controversies over the withdrawal of medical treatment at the end of life. In re Quinlan1 arose at a time when the rules for decisionmaking for incompetent patients were still unformed and inchoate. It set the framework of analysis for most of the subsequent development in the field. Schiavo,2 on the other hand, arose over a di...

We compare two types of knowledge representations for data mining: decision trees and knowledge rules, and three mining methods. We show that the decision tree representation and the knowledge rules representation are semantically equivalent. The ID3 algorithm by Quinlan has limited generalization power because it uses only a very simple generalization function of partial attribute removal type...

This paper proposes the use of inductive inference "decision trees" for isolated digit recognition. The aim of this research is to demonstrate that inductive learning can provide an alternative approach to existing automatic speech recognition techniques such as Dynamic Time Warping (DP), Hidden Markov Modelling (HMM) and Neural Networks (NN). The construction of the decision tree is based on C...