% TeX file: 5.2 Discussion of Future Work

\par
% TeX file: 5.2 Discussion of Future Work
\par One idea that arose during the preliminary stages of the project that has
now become a work currently in progress is the implementation of support vector
machines. A support vector machine is a powerful algorithm used for prediction
in machine learning, often for classification purposes. In theory, it can allow
the user to draw flexible yet robust boundaries between data points given some
criterion. If properly implemented, models generated by this algorithm could
shed light on an entire class of inquiries, like what parts of the brain would
activate given increasing parametric gains and losses, and vice versa. The
mechanism by which support vector machines work make such topics natural to work
with, while also introducing an additional degree of resolution and confidence
in findings that pertain to these topics.
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Add bit on support vector machine implementation
Add bit on support vector machine implementation