OBJECTIVES To compare chi-squared automatic interaction detection (CHAID) classification trees vs the seventh edition of the TNM classification for patients with head and neck squamous cell carcinoma and to assess whether CHAID classification trees might improve results obtained with the TNM classification. DESIGN Patient disease was classified according to CHAID classification trees and the ...

The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this texts use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors study of tree methods. Classification and Regression Trees reflects these two sides...

It is the goal of classification and regression to build a data mining model that can be used for prediction. To construct such a model, we are given a set of training records, each having several attributes. These attributes can either be numerical (for example, age or salary) or categorical (for example, profession or gender). There is one distinguished attribute, the dependent attribute; the...

One method for building classification trees is to choose split variables by maximising expected entropy. This can be extended through the application of imprecise probability by replacing instances of expected entropy with the maximum possible expected entropy over credal sets of probability distributions. Such methods may not take full advantage of the opportunities offered by imprecise proba...

classification trees (j48) were induced to predict the habitat requirements of tench (tinca tinca). 306 datasets were used for the given fish during 8 years in the river basins in flanders (belgium). the input variables consisted of the structural-habitat (width, depth, gradient slope and distance from the source) and physic chemical (ph, dissolved oxygen, water temperature and electric conduct...

proper forest management needs quantitative and precise estimates of forest stands characteristics. remotely sensed imageries, due to accurate and broad spatial information, has become a cost-effective tool in forest management. classification of forest attributes and generation of thematic maps are among the common applications of remote sensing. the objective of this study was to optimize the...

Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. The most comprehensible decision trees have been designed for perfect symbolic data. Classical crisp decision trees (DT) are widely applied to classification t...

Multilayer Perceptrons and trained classification trees are two very different techniques which have recently become popular. Given enough data and time, both methods are capable of performing arbitrary nonlinear classification. We first consider the important differences between multilayer Perceptrons and classification trees and conclude that there is not enough theoretical basis for the clea...

StatMod provides an easy-to-use and inexpensive tool for spatially applying the classification rules generated from the CT algorithm in S-PLUS. While the focus of this article was to use StatMod for classification trees, StatMod functions in a similar manner for regression trees. Classification trees are appropriate for discriminating distinct classes such as land cover. In a regression tree, t...