Journal of Proteomics & Bioinformatics
Open Access

Alexander Kurosky

Publications

• Research Article
  Diagnostics for Statistical Variable Selection Methods for Prediction of Peptic Ulcer Disease in Helicobacter pylori Infection
  Author(s): Hyunsu Ju, Allan R Brasier, Alexander Kurosky, Bo Xu, Victor E Reyes and David Y Graham Hyunsu Ju, Allan R Brasier, Alexander Kurosky, Bo Xu, Victor E Reyes and David Y Graham
  
  Background: The development of accurate classification models depends upon the methods used to identify the most relevant variables. The aim of this article is to evaluate variable selection methods to identify important variables in predicting a binary response using nonlinear statistical models. Our goals in model selection include producing non-overfitting stable models that are interpretable, that generate accurate predictions and have minimum bias. This work was motivated by data on clinical and laboratory features of Helicobacter pylori infections obtained from 60 individuals enrolled in a prospective observational study. Results: We carried out a comprehensive performance comparison of several nonlinear classification models over the H. pylori data set. We compared variable selection results by Multivariate Adaptive Regression Splines (MARS), Logistic Regression with regulariza.. View More»
  DOI: 10.4172/jpb.1000308

  Abstract PDF

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