Description
Task 6:Machine Learning Support Vector Machine Classifier
Problem Statement:
Spam email classification using Support Vector Machine: In this assignment you will use a SVM to classify emails into spam or non-spam categories. And report the classification accuracy for various SVM parameters and kernel functions.
Data Set Description:
An email is represented by various features like frequency of occurrences of certain keywords, length of capitalized words etc. A data set containing about 4601 instances are available in this link (data folder): Link
The data format is also described in the above link. You have to randomly pick 70% of the data set as training data and the remaining as test data.
Assignment Tasks:
In this assignment you can use any SVM package to classify the above data set. You should use one of the following languages: c/C++/Java/Python. You have to study performance of the SVM algorithms.
Report Format :
The report should contain the following sections:
- Mention library which you are using.
- Methodology: Details of the SVM package used.
- Experimental Results:
- You have to use each of the following three kernel functions (a) Linear, (b) Quadratic, (c) RBF.
- For each of the kernels, you have to report training and test set classification accuracy for the best value of generalization constant C. The best C value is the one which provides the best test set accuracy that you have found out by trial of different values of C. Report accuracies in the form of a
For Reference :
