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pl:dydaktyka:ml:lab9 [2017/07/17 10:08] |
pl:dydaktyka:ml:lab9 [2019/06/27 15:50] (aktualna) |
| ====== Support Vector Machines ====== |
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| Ćwiczenia bazujące na materiałach Andrew Ng.\\ |
| Przed zajęciami przejrzyj wykłady [[https://class.coursera.org/ml/lecture/preview|XII]] \\ |
| {{:pl:dydaktyka:ml:ex6.pdf|Instructions}} in English. |
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| Ćwiczenia do pobrania (files to download): {{:pl:dydaktyka:ml:svm.zip|SVM}} |
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| ===== Lista i opis plików ===== |
| Pliki oznaczone znakiem wykrzyknika (:!:) należy wypełnić własnym kodem |
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| * 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 |
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