A Hybrid Approach for Modeling High Dimensional Medical Data. Alok Sharma, Godfrey C. Onwubolu. IWIM, Prague, 2007.

 Article (in pdf)

Abstract. This work presents the application of hybrid PCA and LDA to modeling high dimensional medical data, which is a real-life problem. For modeling and classifying medical data, we adopted this combination of two stage PCA and LDA procedure which is also known as Fisherface technique. During the training phase we applied this combination for extracting features from medical data. In the classification stage we introduced weighting ratio which is used with the conventional Euclidean distance measure to classify a given sample. For brevity we call this technique the weighted distance Fisherface technique. The presented technique shows promising results for medical data when compared with standard GMDH technique; in the two problems taken from the machining learning databases, the presented approach performed better than the standard GMDH.

Keywords. Dimensionality reduction, inductive modeling, classification, PCA, LDA.

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