Generally classifiers tend to overfit if there is noise in the training data or there are missing values. Ensemble learning methods are often used to improve a classifier’s classification accuracy. Most ensemble learning approaches aim to improve the classification accuracy of decision trees. However, alternative classifiers to decision trees exist. The recently developed Random Prism ensemble ...

 Automatic pattern classification is a very important field of artificial intelligence. For these kind of tasks different techniques have been used. In this work a combination of decision trees and self-organizing neural networks is presented as an alternative to attack the problem. For the construction of these trees growth processes are applied. In these processes, the evaluation of classifi...

Among classification problems multi-modal problems form an important category. They naturally arise in many fields when a single class can occupy disjoint areas in the feature space. They are particularly hard to solve for traditional classification techniques. Decision tree Classifiers(DTCs) in principle are able to solve such problems by the recursive nature of their algorithm. In principle, ...

MOTIVATION Phylogenetic analysis of protein sequences is widely used in protein function classification and delineation of subfamilies within larger families. In addition, the recent increase in the number of protein sequence entries with controlled vocabulary terms describing function (e.g. the Gene Ontology) suggests that it may be possible to overlay these terms onto phylogenetic trees to au...

Mainly understandable decision trees have been intended for perfect symbolic data. Conventional crisp decision trees (DT) are extensively used for classification purpose. However, there are still many issues particularly when we used the numerical (continuous valued) attributes. Structured continuouslabel classification is one type of classification in which the label is continuous in the data....

Background: Fertility is one of the important subjects in public health and demographic studies which affects population growth. The main objective of this paper was to introduce and apply a tree model to classify the ideal number of children and children ever born in the study of "Marriage and Fertility Attitudes of Married 15-49 Years Old Women in Semnan Province in Iran, 2012". Methods: Cla...

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...

The advent of gene chips has led to a promising technology for cell, tumor, and cancer classification. We exploit and expand the methodology of recursive partitioning trees for tumor and cell classification from microarray gene expression data. To improve classification and prediction accuracy, we introduce a deterministic procedure to form forests of classification trees and compare their perf...