Abstract: This paper proposes a pattern recognition method for the fault diagnosis of machinery based on an enhanced trace ratio linear discriminant analysis (ETR-LDA) algorithm. It is an extension of ...
Abstract: Linear discriminant analysis (LDA) based classifiers tend to falter in many practical settings where the training data size is smaller than, or comparable to, the number of features. As a ...
This package includes functions for computing and visualizing generalized canonical discriminant analyses and canonical correlation analysis for a multivariate linear model (MLM). The goal is to ...
ABSTRACT: Bankruptcies result in significant financial and social losses for all stakeholders of companies each year. For this reason, researchers have been working for decades to develop effective ...
Decision Trees theory is a method used in machine learning and data analysis that allows building decision-making models with tree-shaped hierarchy. In each node of the tree, a certain criterion is ...
The problem of classification in situations where the assumption of normality in the data is violated, and there are non-linear clustered structures in the dataset is addressed. A robust nonparametric ...
Discriminant-type analyses arise from the need to classify samples based on their measured characteristics (variables), usually with respect to some observable property. In the case of samples that ...
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