Support Vector Machines

Ćwiczenia bazujące na materiałach Andrew Ng.
Przed zajęciami przejrzyj wykłady XII
Instructions in English.

Ćwiczenia do pobrania (files to download): SVM

Lista i opis plików

Pliki oznaczone znakiem wykrzyknika (:!:) należy wypełnić własnym kodem

  • ex6.m - Octave script for the first half of the exercise
  • ex6data1.mat - Example Dataset 1
  • ex6data2.mat - Example Dataset 2
  • ex6data3.mat - Example Dataset 3
  • svmTrain.m - SVM training function
  • svmPredict.m - SVM prediction function
  • plotData.m - Plot 2D data
  • visualizeBoundaryLinear.m - Plot linear boundary
  • visualizeBoundary.m - Plot non-linear boundary
  • linearKernel.m - Linear kernel for SVM
  • :!: gaussianKernel.m - Gaussian kernel for SVM
  • :!: dataset3Params.m - Parameters to use for Dataset 3
  • ex6 spam.m - Octave script for the second half of the exercise
  • spamTrain.mat - Spam training set
  • spamTest.mat - Spam test set
  • emailSample1.txt - Sample email 1
  • emailSample2.txt - Sample email 2
  • spamSample1.txt - Sample spam 1
  • spamSample2.txt - Sample spam 2
  • vocab.txt - Vocabulary list
  • getVocabList.m - Load vocabulary list
  • porterStemmer.m - Stemming function
  • readFile.m - Reads a file into a character string
  • submit.m - Submission script that sends your solutions to our servers
  • submitWeb.m - Alternative submission script
  • :!: processEmail.m - Email preprocessing
  • :!: emailFeatures.m - Feature extraction from emails
pl/dydaktyka/ml/lab9.txt · ostatnio zmienione: 2017/07/17 08:08 (edycja zewnętrzna)
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