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Classification with Support Vector Machines PDF Print E-mail
Written by Simeone Zomer   
Classification is very common task in chemometrics and several methods are reported in the literature for solving this type of problems. The choice of the most appropriate method depends on the specific nature of the problem. For example how many classes, objects and variables describe the dataset, what is the expected complexity of the boundaries between the classes (e.g. from exploratory analysis), what is the noise level and the fraction of outliers in the data ect. In simpler cases (e.g. linear boundaries, many samples and fewer variables) many algorithms may perform satisfactorily, whereas for most complicated cases the choice for reaching optimal performance is usually more restricted.
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