\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: