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Tobias Arndt 4 years ago
parent bad8e42630
commit cb9777f037
3 changed files with 40 additions and 33 deletions
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35
TeX/Plots/gen_dropout.tex
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@ -4,8 +4,8 @@ legend image code/.code={
\draw[mark repeat=2,mark phase=2]
plot coordinates {
(0cm,0cm)
(0.3cm,0cm) %% default is (0.3cm,0cm)
(0.6cm,0cm) %% default is (0.6cm,0cm)
(0.15cm,0cm) %% default is (0.3cm,0cm)
(0.3cm,0cm) %% default is (0.6cm,0cm)
};%
}
}
@ -15,7 +15,8 @@ plot coordinates {
\begin{axis}[legend cell align={left},yticklabel style={/pgf/number format/fixed,
/pgf/number format/precision=3},tick style = {draw = none}, width = \textwidth,
height = 0.6\textwidth, ymin = 0.988, legend style={at={(0.9825,0.0175)},anchor=south east},
xlabel = {epoch}, ylabel = {Classification Accuracy}, cycle list/Dark2]
xlabel = {epoch}, ylabel = {Classification Accuracy}, cycle
list/Dark2, every axis plot/.append style={line width =1.25pt}]
\addplot table
[x=epoch, y=val_accuracy, col sep=comma, mark = none]
{Plots/Data/adam_datagen_full_mean.log};
@ -47,20 +48,20 @@ plot coordinates {
\vspace{.25cm}
\end{subfigure}
\begin{subfigure}[h]{1.0\linewidth}
\begin{tabu} to \textwidth {@{} l *6{X[c]} @{}}
\multicolumn{7}{c}{Classification Accuracy}\Bstrut
\\\hline
&\textsc{Adam}&D. 0.2&D. 0.4&G.&G.+D.~0.2&G.+D.~0.4 \Tstrut \Bstrut
\\\hline
mean&0.9914&0.9918&0.9928&0.9937&0.9938&0.9940 \Tstrut \\
max& \\
min& \\
\multicolumn{7}{c}{Training Accuracy}\Bstrut
\\\hline
mean&0.9994&0.9990&0.9989&0.9967&0.9954&0.9926 \Tstrut \\
max& \\
min& \\
\begin{tabu} to \textwidth {@{}lc*5{X[c]}@{}}
\Tstrut \Bstrut & \textsc{\,Adam\,} & D. 0.2 & D. 0.4 & G. &G.+D.\,0.2 & G.+D.\,0.4 \\
\hline
\multicolumn{7}{c}{Classification Accuracy}\Bstrut \\
\cline{2-7}
mean \Tstrut & 0.9914 & 0.9923 & 0.9930 & 0.9937 & 0.9938 & 0.9943 \\
max & 0.9926 & 0.9930 & 0.9934 & 0.9946 & 0.9955 & 0.9956 \\
min & 0.9887 & 0.9909 & 0.9922 & 0.9929 & 0.9929 & 0.9934 \\
\hline
\multicolumn{7}{c}{Training Accuracy}\Bstrut \\
\cline{2-7}
mean \Tstrut & 0.9994 & 0.9991 & 0.9989 & 0.9967 & 0.9954 & 0.9926 \\
max & 0.9996 & 0.9996 & 0.9992 & 0.9979 & 0.9971 & 0.9937 \\
min & 0.9992 & 0.9990 & 0.9984 & 0.9947 & 0.9926 & 0.9908 \\
\end{tabu}
\caption{Mean and maximum accuracy after 48 epochs of training.}
\end{subfigure}

33
TeX/Plots/pfg_test.tex
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@ -30,7 +30,8 @@ plot coordinates {
\begin{axis}[legend cell align={left},yticklabel style={/pgf/number format/fixed,
/pgf/number format/precision=3},tick style = {draw = none}, width = \textwidth,
height = 0.6\textwidth, ymin = 0.988, legend style={at={(0.9825,0.0175)},anchor=south east},
xlabel = {epoch}, ylabel = {Classification Accuracy}, cycle list/Dark2]
xlabel = {epoch}, ylabel = {Classification Accuracy}, cycle
list/Dark2, every axis plot/.append style={line width =1.25pt}]
% \addplot [dashed] table
% [x=epoch, y=accuracy, col sep=comma, mark = none]
% {Data/adam_datagen_full.log};
@ -68,26 +69,26 @@ plot coordinates {
\vspace{.25cm}
\end{subfigure}
\begin{subfigure}[h]{1.0\linewidth}
\begin{tabu} to \textwidth {@{} l *6{X[c]} @{}}
\multicolumn{7}{c}{Classification Accuracy}\Bstrut
\\\hline
&\textsc{Adam}&D. 0.2&D. 0.4&G.&G.+D.~0.2&G.~,D.~0.4 \Tstrut \Bstrut
\\\hline
mean&0.9994&0.9990&0.9989&0.9937&0.9938&0.9940 \Tstrut \\
max& \\
min& \\
\multicolumn{7}{c}{Training Accuracy}\Bstrut
\\\hline
mean&0.9914&0.9918&0.9928&0.9937&0.9938&0.9940 \Tstrut \\
max& \\
min& \\
\begin{tabu} to \textwidth {@{}lc*5{X[c]}@{}}
\Tstrut \Bstrut & \textsc{\,Adam\,} & D. 0.2 & D. 0.4 & G. &G.+D.\,0.2 & G.+D.\,0.4 \\
\hline
\multicolumn{7}{c}{Classification Accuracy}\Bstrut \\
\cline{2-7}
mean \Tstrut & 0.9914 & 0.9923 & 0.9930 & 0.9937 & 0.9938 & 0.9943 \\
max & 0.9926 & 0.9930 & 0.9934 & 0.9946 & 0.9955 & 0.9956 \\
min & 0.9887 & 0.9909 & 0.9922 & 0.9929 & 0.9929 & 0.9934 \\
\hline
\multicolumn{7}{c}{Training Accuracy}\Bstrut \\
\cline{2-7}
mean \Tstrut & 0.9994 & 0.9991 & 0.9989 & 0.9967 & 0.9954 & 0.9926 \\
max & 0.9996 & 0.9996 & 0.9992 & 0.9979 & 0.9971 & 0.9937 \\
min & 0.9992 & 0.9990 & 0.9984 & 0.9947 & 0.9926 & 0.9908 \\
\end{tabu}
\caption{Mean and maximum accuracy after 48 epochs of training.}
\end{subfigure}
\caption{Accuracy for the net given in ... with Dropout (D.),
data generation (G.), a combination, or neither (Default) implemented and trained
with \textsc{Adam}. For each epoch the 60.000 training samples
with \textsc{Adam}. For each epoch the 60.000 training samples
were used, or for data generation 10.000 steps with each using
batches of 60 generated data points. For each configuration the
model was trained 5 times and the average accuracies at each epoch

5
TeX/further_applications_of_nn.tex
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@ -695,6 +695,11 @@ mirroring.
... Additionally mirroring is not used for ... reasons.}
\end{figure}
In order to compare the benefits obtained from implementing these
measures we have trained the network given in ... on the same problem
and implemented different combinations of the measures. The results
are given in Figure~\ref{fig:gen_dropout}. Here it can be seen that ...
\input{Plots/gen_dropout.tex}
\todo{Vergleich verschiedene dropout größen auf MNSIT o.ä., subset als

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