Description: Part1. Achieve a k-nearest neighbor classifier, Part 2. Achieve a least-squares classifier, Part 3. Implement a support vector machine classifier, Part 4. Different data sets used in the cross-validation to select individual parameters of the algorithm
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classifier
..........\crossvalidation.m
..........\digits38_parameters.mat
..........\g50c_parameters.mat
..........\knnclassifier.m
..........\lsclassifier.m
..........\softsvm.m
..........\text_parameters.mat
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