dekker.one
Group work for a Monash Research Methods course
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mini_proj/report/waldo.tex
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mini_proj/report/waldo.tex
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various different classification methods from more classical machine
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learning, like naive Bayes classifiers, to the currently state of the art,
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Neural Networks. In \Cref{sec:background} we will introduce the different
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classification methods, \Cref{sec:methods} will explain the way in which
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classification methods, \Cref{sec:method} will explain the way in which
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these methods are trained and how they will be evaluated, in
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\Cref{sec:results} will discuss the results, and \Cref{sec:conclusion} will
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offer our final conclusions.
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\todo{This paper is mad \cite{Kotsiantis2007}.}
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\section{Methods}
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\section{Method} \label{sec:method}
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% Kelvin Start
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\subsection{Benchmarking}\label{benchmarking}
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statistics include:
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\begin{itemize}
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\tightlist
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\item
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\textbf{Accuracy:}
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\[a = \dfrac{|correct\ predictions|}{|predictions|} = \dfrac{tp + tn}{tp + tn + fp + fn}\]