1. Classification of biomedical spectra using stochastic feature selection
- Creator:
- Pizzi, Nick J.
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Biomedical spectra, classification, multilayer perceptron, probabilistic neural network, and feature selection
- Language:
- English
- Description:
- When dealing with the curse of dimensionality (small sample size with many dimensions), feature selection is an important preprocessing strategy for the analysis of biomedical data. This issue is particularly germane to the classification of high-dimensional class-labeled biomedical spectra as is often acquired from magnetic resonance and infrared spectrometers. A technique is presented that stochastically selects feature subsets with varying cardinality for automated discrimination using two types of neural network classifiers. The results are benchmarked against classifiers using the entire feature set with and without averaging. Stochastic feature subset selection had significantly fewer misclassifications than either of the benchmarks.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public