CS 848 Assignment -- Classification Methods

<h1>CS 848 Assignment -- Classification Methods</h1>

<h3>Gordon V. Cormack</h3>

Use a data compression model, and another contrasting method, to do classification
for an information retrieval task, such as spam filtering, authorship detection,
language categorization, vandalism detection on wikis, etc.
<p>
Design and execute an experiment that measures and compares the effectiveness
of your approaches.  In doing so you will have to acquire some
data (e.g. some email from your inbox, or something you gather from
the Web, or a standard dataset) and measure the result.  
Make sure that the data used to measure the result plays no role in the design,
tuning, or training of your methods.  
<p>
Your approach need not be grandiose.  It is perfectly acceptable,
for example, to collect a few dozen messages, split them into
training and test sets, and use the method described in class.
You may use any compression model you like, including DMC, 
PPM, or any popular compression software.  You may use any other
classifier you like, including off-the-shelf packages such
as Liblinear, Weka, LibSVM, SVMlight, lr-trirls, or any number
of spam filters.  You may implement your own if you wish.
<p>
You should write two-to-four pages describing your methods,
the experiment you designed including the source of the
data, and measured results.  Your write-up should include
at least one paragraph of observations and discussion.