[Solved] CS312 Lab 6-Reinforcement Learning

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Machine Learning Support Vector Machine Classifier

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): LinkThe 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.

Submission:

Please submit a zip file <Group_number>.zip with the following contents

  1. Program: <group_number>.<extension> (e.g., 1.c/cpp)
  2. Report: <group_number>.<extension> (e.g., 1.pdf). Report should be in pdf format.
  3. Readme file: readme.txt (Execution details)

Report Format :

The report should contain the following sections:

  1. Mention library which you are using.
  2. Methodology: Details of the SVM package used.
  3. Experimental Results:i. You have to use each of the following three kernel functions (a) Linear, ( b) Quadratic, (c) RBF.ii. 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 comparison table, along with the values of C.

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[Solved] CS312 Lab 6-Reinforcement Learning[Solved] CS312 Lab 6-Reinforcement Learning
$25