A classification decision must include the degree of confidence in that decision. We have
modified the binary classification method Discriminant Partial Least Squares (DPLS) to …

The identification and assessment of prognostic factors is one of the major tasks in clinical
research. The assessment of one single prognostic factor can be done by recently …

In this study, it is aimed that comparing logistic regression model with classification tree
method in determining social-demographic risk factors which have effected depression …

Rule-based classification using classification tree analysis (CTA) is increasingly applied to
remotely sensed data. CTA employs splitting rules to construct decision trees using training …

Abstract In this study, Regression Tree Analysis (RTA) was used to predict and to determine
the most important variables in predicting the slaughter weight of Ross 308 broiler chickens …

The application of supervised pattern recognition methodology is becoming important within
chemistry. The aim of the study is to compare classification method accuracies by the use of …

Artificial-intelligence and machine-learning algorithms are gaining the attention of
researchers in the field of groundwater modelling. This study explored and assessed a new …

Rankings and partial rankings are ubiquitous in data analysis, yet there is relatively little
work in the classification community that uses the typical properties of rankings. We review …

Abstract Framework of this paper is statistical data editing, specifically how to edit or impute
missing or contradictory data and how to merge two independent data sets presenting some …

La regresión lineal es el método más usado en estadıstica para predecir valores de
variables continuas debido a su fácil interpretación, pero en muchas situaciones los …