Classification of Biomedical Spectra Using Fuzzy Interquartile Encoding and Stochastic Feature Selection
Nick J. Pizzi, Mark D. Alexiuk, Witold Pedrycz · 2007
Accurate classification of biomedical spectra is often difficult due to the large number of features, which tends to have a confounding effect. We present a strategy where the original spectral feature space is transformed using a fuzzy set theoretic method, which analyzes the features' interquartile ranges, coupled with a stochastic feature selection mechanism, which identifies highly discriminatory feature subsets. We demonstrate the effectiveness of this strategy using biofluid data acquired from a magnetic resonance spectrometer