#Email-Spam-Filter

Programming Exercise 6 in Machine Learning course by Andrew Ng on Coursera. In this exercise one shall learn to use support vector machines (SVMs) to build a spam classifier.

The details of this assignment are described in tutorial.pdf

The codes are written in GNU Octave. For further info on Octave please see http://www.gnu.org/software/octave/

This set includes the following functions:

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
processEmail.m - Email preprocessing
emailFeatures.m - Feature extraction from emails