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\pgfplotsset{
compat=1.11,
legend image code/.code={
\draw[mark repeat=2,mark phase=2]
plot coordinates {
(0cm,0cm)
(0.15cm,0cm) %% default is (0.3cm,0cm)
(0.3cm,0cm) %% default is (0.6cm,0cm)
};%
}
}
\begin{figure}
\begin{subfigure}[h]{\textwidth}
\begin{tikzpicture}
\begin{axis}[legend cell align={left},yticklabel style={/pgf/number format/fixed,
/pgf/number format/precision=3},tick style = {draw = none}, width = 0.975\textwidth,
height = 0.6\textwidth, ymin = 0.885, legend style={at={(0.9825,0.0175)},anchor=south east},
xlabel = {Epoch}, ylabel = {Test Accuracy}, cycle
list/Dark2, every axis plot/.append style={line width
=1.25pt}]
% [tick style = {draw = none}, width = \textwidth,
% height = 0.6\textwidth, ymin = 0.905, legend style={at={(0.9825,0.75)},anchor=north east},
% xlabel = {epoch}, ylabel = {Classification Accuracy}]
% \addplot table
% [x=epoch, y=val_accuracy, col sep=comma, mark = none]
% {Figures/Data/adagrad.log};
% \addplot table
% [x=epoch, y=val_accuracy, col sep=comma, mark = none]
% {Figures/Data/adadelta.log};
% \addplot table
% [x=epoch, y=val_accuracy, col sep=comma, mark = none]
% {Figures/Data/adam.log};
\addplot table
[x=epoch, y=val_accuracy, col sep=comma, mark = none]
{Figures/Data/Adagrad.mean};
\addplot table
[x=epoch, y=val_accuracy, col sep=comma, mark = none]
{Figures/Data/Adadelta.mean};
\addplot table
[x=epoch, y=val_accuracy, col sep=comma, mark = none]
{Figures/Data/Adam.mean};
\addplot table
[x=epoch, y=val_accuracy, col sep=comma, mark = none]
{Figures/Data/SGD_00.mean};
\addplot table
[x=epoch, y=val_accuracy, col sep=comma, mark = none]
{Figures/Data/SGD_09.mean};
\addlegendentry{\footnotesize{\textsc{AdaGrad}}}
\addlegendentry{\footnotesize{\textsc{Adadelta}}}
\addlegendentry{\footnotesize{\textsc{Adam}}}
\addlegendentry{\footnotesize{\textsc{Sgd}}}
\addlegendentry{\footnotesize{Momentum}}
\end{axis}
\end{tikzpicture}
\caption{Test accuracies during training}
\vspace{.25cm}
\end{subfigure}
% \begin{subfigure}[b]{\textwidth}
% \begin{tikzpicture}
% \begin{axis}[tick style = {draw = none}, width = \textwidth,
% height = 0.6\textwidth, ymax = 0.5,
% xlabel = {epoch}, ylabel = {Error Measure\vphantom{y}},ytick ={0,0.1,0.2,0.3,0.4,0.45,0.5}, yticklabels =
% {0,0.1,0.2,0.3,0.4,\phantom{0.94},0.5}]
% \addplot table
% [x=epoch, y=val_loss, col sep=comma, mark = none] {Figures/Data/adagrad.log};
% \addplot table
% [x=epoch, y=val_loss, col sep=comma, mark = none] {Figures/Data/adadelta.log};
% \addplot table
% [x=epoch, y=val_loss, col sep=comma, mark = none] {Figures/Data/adam.log};
% \addlegendentry{\footnotesize{ADAGRAD}}
% \addlegendentry{\footnotesize{ADADELTA}}
% \addlegendentry{\footnotesize{ADAM}}
% \addlegendentry{SGD$_{0.01}$}
% \end{axis}
% \end{tikzpicture}
% \caption{Performance metrics during training}
% \vspace{.25cm}
% \end{subfigure}
\begin{subfigure}[b]{1.0\linewidth}
\begin{tabu} to \textwidth {@{}l*5{X[c]}@{}}
\Tstrut \Bstrut &\textsc{AdaGrad}& \textsc{AdaDelta}&
\textsc{Adam} & \textsc{Sgd} & Momentum \\
\hline
\Tstrut Accuracy &0.9870 & 0.9562 & 0.9925 & 0.9866 & 0.9923 \\
\Tstrut Loss &0.0404 & 0.1447 & 0.0999 & 0.0403 & 0.0246 \\
\end{tabu}
% \begin{tabu} to \textwidth {@{} *3{X[c]}c*3{X[c]} @{}}
% \multicolumn{3}{c}{Classification Accuracy}
% &~&\multicolumn{3}{c}{Error Measure}
% \\\cline{1-3}\cline{5-7}
% \textsc{AdaGad}&\textsc{AdaDelta}&\textsc{Adam}&&\textsc{AdaGrad}&\textsc{AdaDelta}&\textsc{Adam}
% \\\cline{1-3}\cline{5-7}
% 1&1&1&&1&1&1
% \end{tabu}
\caption{Performace metrics after 50 epochs}
\end{subfigure}
\caption[Performance Comparison of Training Algorithms]{
Average performance metrics of the neural network given in
Figure~\ref{fig:mnist_architecture} trained 5 times for 50 epochs
using different optimization algorithms.}
\label{fig:comp_alg}
\end{figure}
%%% Local Variables:
%%% mode: latex
%%% TeX-master: "../main"
%%% End: