difference aspects of multinomial statistical modelings and its classifications has been studied so far. in these type of problems y is the qualitative random variable with t possible states which are considered as classifications. the goal is prediction of y based on a random vector x ? ir^m. many methods for analyzing these problems were considered. one of the modern and general method of cla...

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Classification and regression trees are machine-learning methods for constructing prediction models from data. The models are obtained by recursively partitioning the data space and fitting a simple prediction model within each partition. As a result, the partitioning can be represented graphically as a decision tree. Classification trees are designed for dependent variables that take a finite ...

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...

Abstract Classification and regression trees, as well their variants, are off-the-shelf methods in Machine Learning. In this paper, we review recent contributions within the Continuous Optimization Mixed-Integer Linear paradigms to develop novel formulations research area. We compare those terms of nature decision variables constraints required, optimization algorithms proposed. illustrate how ...

Background: Due to the importance of medical studies, researchers of this field should be familiar with various types of statistical analyses to select the most appropriate method based on the characteristics of their data sets. Classification and regression trees (CARTs) can be as complementary to regression models. We compared the performance of a logistic regression model and a CART in predi...