Diagnosing Anorexia Based on Partial Least Squares, Back Propagation Neural Network, and Support Vector Machines


Support vector machine (SVM), as a novel type of learning machine, for the first time, was used to develop a predictive model for early diagnosis of anorexia. It was based on the concentration of six elements (Zn, Fe, Mg, Cu, Ca, and Mn) and the age extracted from 90 cases. Compared with the results obtained from two other classifiers, partial least squares… (More)
DOI: 10.1021/ci049877y


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