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

classifier
..........\crossvalidation.m
..........\digits38_parameters.mat
..........\g50c_parameters.mat
..........\knnclassifier.m
..........\lsclassifier.m
..........\softsvm.m
..........\text_parameters.mat

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．