# A Pilot Study of Stacked Autoencoders for Ship Mode Classification
## 5 Experimental Results and Discussion  
### Experimental Results  
This section assesses the performance of the models by comparing the model structures used in the comparison experiments. For this analysis, 200 epochs of training were performed on all models, and the batch size was 64. Additionally, the evaluation metrics were used to evaluate the performance of each model structure, and the latent layer size suitable for each model structure was found. Comparative evaluations were also performed on the models that showed the best performance for each model structure. Table 5 lists the evaluation results for the (5-32) structure. The accuracy performance is stable regardless of the latent layer size. However, the FPR and MCC values are affected by the latent layer size. A latent layer size of 9 produces the best performance in the (5-32) structure. Table 6 shows the evaluation results for the (5-64) structure. Different from the evaluation results for the (5-32) structure, there is a significant difference in accuracy. The performance rapidly worsens when the latent layer size is 6. However, the FPR's performance is exceptional. The performance comparison results obtained using MCC indicate that the best performance occurs when the latent layer size is 12. Table 7 illustrates the evaluation results for the (5-128) structure. The TPR performance is best when the latent layer size is 12, and the FPR performance is best when the latent layer size is 6. However, the MCC and accuracy performance are best when the latent layer size is 9. \begin{table}
\begin{tabular}{c c c c c} \hline
**Latent Layer Size** & **TPR** & **FPR** & **MCC** & **Accuracy** \\ \hline
3 & 0.9141 & 0.0867 & 0.8692 & 0.9469 \\
6 & 0.4924 & 0.0355 & 0.8470 & 0.9372 \\
9 & 0.9556 & 0.1094 & 0.8782 & 0.9503 \\
12 & 0.9077 & 0.0741 & 0.8867 & 0.9538 \\ \hline \end{tabular}
\end{table} 
Table 6: Evaluation results of the (5–64) structure. \begin{table}
\begin{tabular}{c c c c c} \hline
**Latent Layer Size** & **TPR** & **FPR** & **MCC** & **Accuracy** \\ \hline
3 & 0.8656 & 0.0742 & 0.8798 & 0.9510 \\
6 & 0.7848 & 0.0499 & 0.8831 & 0.9522 \\
9 & 0.9541 & 0.0974 & 0.8877 & 0.9541 \\
12 & 0.8392 & 0.0597 & 0.8836 & 0.9525 \\ \hline \end{tabular}
\end{table} 
Table 5: Evaluation results of the (5–32) structure. Table 8 lists the evaluation results for the (7-64) structure. The TPR performance is the best when the latent layer size is 3, and the FPR performance is the best when the latent layer size is 9. However, the MCC and accuracy performance are at their best when the latent layer size is 12. Table 9 shows the evaluation results for the (7-128) structure. The TPR performance is the best when the latent layer size is 9, and the FPR, MCC, and accuracy performance are the best when the latent layer size is 6. Table 10 illustrates the best model structures based on MCC scores. In the comparison results, the MCC evaluation metric confirms that the (5-128) structure is the best at classifying the ship operating mode when the latent layer size is 9. Furthermore, Figure 5 shows the MCC value according to the latent layer size of the models used in the comparison experiments. \begin{table}
\begin{tabular}{c c c c c} \hline
**Latent Layer Size** & **TPR** & **FPR** & **MCC** & **Accuracy** \\ \hline
3 & 0.9440 & 0.1356 & 0.8581 & 0.9423 \\
6 & 0.8436 & 0.0676 & 0.8926 & 0.9559 \\
9 & 0.8253 & 0.0219 & 0.8981 & 0.9581 \\
12 & 0.8470 & 0.0319 & 0.9036 & 0.9604 \\ \hline \end{tabular}
\end{table} 
Table 8: Evaluation results of the (7–64) structure. \begin{table}
\begin{tabular}{c c c c c} \hline
**Latent Layer Size** & **TPR** & **FPR** & **MCC** & **Accuracy** \\ \hline
3 & 0.9367 & 0.0792 & 0.8867 & 0.9538 \\
6 & 0.8750 & 0.0518 & 0.8980 & 0.9583 \\
9 & 0.9319 & 0.0585 & 0.8979 & 0.9583 \\
12 & 0.8947 & 0.0556 & 0.8955 & 0.9573 \\ \hline \end{tabular}
\end{table} 
Table 9: Evaluation results of the (7–128) structure.