Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Feature And Model Selection In Feedforward Neural Networks, Jean M. Steppe
Feature And Model Selection In Feedforward Neural Networks, Jean M. Steppe
Theses and Dissertations
This research advances feature and model selection for feedforward neural networks. Feature selection involves determining a good feature subset given a set of candidate features. Model selection involves determining an appropriate architecture number of middle nodes for the neural network. Specific advances are made in neural network feature saliency metrics used for evaluating or ranking features, statistical identification of irrelevant noisy features, and statistical investigation of reduced neural network architectures and reduced feature subsets. New feature saliency metrics are presented which provide a more succinct quantitative measure of a features importance than other similar metrics. A catalogue of feature saliency …
A Comparison Of Variable Selection Criteria For Multiple Linear Regression: A Third Simulation Study, Ertem Mutlu
A Comparison Of Variable Selection Criteria For Multiple Linear Regression: A Third Simulation Study, Ertem Mutlu
Theses and Dissertations
The goal of this thesis research is to introduce and study a modification of Millers Method which we call the Modified-Millers method MM method, study two step subset selection procedures, these of which apply Millers Method in the first step and employs another method Minimum MSE or Minimum Sp or Minimum Cp in the second step and these of which employ another method Minimum MSE or Minimum Sp or Minimum Cp in the first step and applies Millers Method in the second step. The results of all techniques will be compared including the results of the previous simulation studies done …