Dimensionality Reduction in the Creation of Classifiers and the Effects of Correlation, Cluster Overlap, and Modelling Assumptions.
Discriminant analysis and random forests are used to create models for classification. The number of variables to be tested for inclusion in a model can be large. The goal of this work was to create an efficient and effective selection program. The first method used was based on the work of others...
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| Language: | en |
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2011
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| Online Access: | http://hdl.handle.net/10214/2933 |