We propose a new algorithm for learning isotonic classification trees. It relabels non-monotone leaf nodes by performing the isotonic regression on the collection of leaf nodes. In case two leaf nodes with a common parent have the same class after relabeling, the tree is pruned in the parent node. Since we consider problems with ordered class labels, all results are evaluated on the basis of L1...

Algorithms for learning cIassification trees have had successes in artificial intelligence and statistics over many years. This paper outlines how a tree learning algorithm can be derived using Bayesian statistics. This iutroduces Bayesian techniques for splitting, smoothing, and tree averaging. The splitting rule is similar to QuinIan’s information gain, while smoothing and averaging replace p...

Bellows TS and Fisher TW (eds.) (1999) Handbook of Biological Control: Principles and Applications of Biological Control. San Diego: Academic Press. Clausen CP (ed.) (1978) Agricultural Research Service: Handbook No. 480: Introduced Parasites and Predators of Arthropod Pests and Weeds: A World Review. Washington, DC: USDA: Agricultural Research Service. DeBach P and Rosen D (1991) Biological Co...

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 ...

This paper proposes a novel Distributed Data Mining (DDM) approach based on the Agents and Artifacts paradigm, as implemented in CArtAgO [9], where artifacts encapsulate data mining tools, inherited from Weka, that agents can use while engaged in collaborative, distributed learning processes. Target hypothesis are currently constrained to decision trees built with J48, but the approach is flexi...

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 ...

Industrial accident analysis is a very challenging task and one of most vital issues in the era of globalization. Discovering the attributes becomes more complex because voluminous factors are associated. We have tried to find the specific attributes and made a cumulative dataset depending on the reliable sources allied to Bangladesh. In the study, we have evaluated a meticulous survey on vario...

Gear drives are one of the most widely used transmission system in many machinery. Sound signals of a rotating machine contain the dynamic information about its health conditions. Not much information available in the literature reporting suitability of sound signals for fault diagnosis applications. Maximum numbers of literature are based on FFT (Fast Fourier Transform) analysis and have its o...

In this work are evaluated features selection methods for breast cancer classification in segmented mammographic lesions using two categories of extracted features (numeric and nominal). Numeric included statistical, shape and texture lesion descriptors, and nominal are related with patient’s associated metadata descriptors (clinical history). Datasets of features vectors were created using six...

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...