# A Fine-Tuning Based Approach for Daily Activity Recognition between Smart Homes
## 4 Results and Evaluation
### Experiments and Results
\begin{table}
\begin{tabular}{c c c c c} \hline  & **Experiment** & **Training Set** & **Test Set** & **Accuracy** \\ \hline Group & Ours\_101 to105 & \(1\times\) HH101 + Fine-tuning(0.2 \(\times\) HH105) & 0.8 \(\times\) HH105 & 0.6899 \\ \cline{2-5}
1 & Comparison\_101 to105 & \(1\times\) HH101 + 0.2 \(\times\) HH105 & 0.8 \(\times\) HH105 & 0.6592 \\ \hline Group & Ours\_101 to109 & \(1\times\) HH101 + Fine-tuning(0.2 \(\times\) HH109) & 0.8 \(\times\) HH109 & 0.7413 \\ \cline{2-5}
2 & Comparison\_101 to109 & \(1\times\) HH101 + 0.2 \(\times\) HH109 & 0.8 \(\times\) HH109 & 0.7004 \\ \hline Group & Ours\_101 to110 & \(1\times\) HH101 + Fine-tuning(0.2 \(\times\) HH110) & 0.8 \(\times\) HH110 & 0.6673 \\ \cline{2-5}
3 & Comparison\_101 to110 & \(1\times\) HH101 + 0.2 \(\times\) HH110 & 0.8 \(\times\) HH110 & 0.6129 \\ \hline Group & Ours\_105 to101 & \(1\times\) HH105 + Fine-tuning(0.2 \(\times\) HH101) & 0.8 \(\times\) HH101 & 0.7664 \\ \cline{2-5}
4 & Comparison\_105 to101 & \(1\times\) HH105 + 0.2 \(\times\) HH101 & 0.8 \(\times\) HH101 & 0.7238 \\ \hline Group & Ours\_105 to109 & \(1\times\) HH105 + Fine-tuning(0.2 \(\times\) HH109) & 0.8 \(\times\) HH109 & 0.7339 \\ \cline{2-5}
5 & Comparison\_105 to109 & \(1\times\) HH105 + 0.2 \(\times\) HH109 & 0.8 \(\times\) HH109 & 0.6943 \\ \hline Group & Ours\_105 to110 & \(1\times\) HH105 + Fine-tuning(0.2 \(\times\) HH110) & 0.8 \(\times\) HH110 & 0.6129 \\ \cline{2-5}
6 & Comparison\_105 to110 & \(1\times\) HH105 + 0.2 \(\times\) HH110 & 0.8 \(\times\) HH110 & 0.5376 \\ \hline Group & Ours\_109 to101 & \(1\times\) HH109 + Fine-tuning(0.2 \(\times\) HH101) & 0.8 \(\times\) HH101 & 0.7468 \\ \cline{2-5}
7 & Comparison\_109 to101 & \(1\times\) HH109 + 0.2 \(\times\) HH101 & 0.8 \(\times\) HH101 & 0.7131 \\ \hline Group & Ours\_109 to105 & \(1\times\) HH109 + Fine-tuning(0.2 \(\times\) HH105) & 0.8 \(\times\) HH105 & 0.6256 \\ \cline{2-5}
8 & Comparison\_109 to105 & \(1\times\) HH109 + 0.2 \(\times\) HH105 & 0.8 \(\times\) HH105 & 0.5949 \\ \hline Group & Ours\_109 to110 & \(1\times\) HH109 + Fine-tuning(0.2 \(\times\) HH110) & 0.8 \(\times\) HH110 & 0.6631 \\ \cline{2-5}
9 & Comparison\_109 to110 & \(1\times\) HH109 + 0.2 \(\times\) HH110 & 0.8 \(\times\) HH110 & 0.6004 \\ \hline Group & Ours\_110 to101 & \(1\times\) HH110 + Fine-tuning(0.2 \(\times\) HH101) & 0.8 \(\times\) HH101 & 0.7877 \\ \cline{2-5}
10 & Comparison\_110 to101 & \(1\times\) HH110 + 0.2 \(\times\) HH101 & 0.8 \(\times\) HH101 & 0.7806 \\ \hline Group & Ours\_110 to105 & \(1\times\) HH110 + Fine-tuning(0.2 \(\times\) HH105) & 0.8 \(\times\) HH105 & 0.5837 \\ \cline{2-5}
11 & Comparison\_110 to105 & \(1\times\) HH110 + 0.2 \(\times\) HH105 & 0.8 \(\times\) HH105 & 0.4776 \\ \hline Group & Ours\_110 to109 & \(1\times\) HH110 + Fine-tuning(0.2 \(\times\) HH109) & 0.8 \(\times\) HH109 & 0.8069 \\ \cline{2-5}
12 & Comparison\_110 to109 & \(1\times\) HH110 + 0.2 \(\times\) HH109 & 0.8 \(\times\) HH109 & 0.7586 \\ \hline \end{tabular}
\end{table} 
Table 5: Experimental setup and results of our method and the comparison method. Figure 8: Results of our method and comparison experiments for accuracy, precision, recall and F1-score at each epoch, based on the source domain as HH105, target domain as HH109. Figure 10: Results of our method and comparison experiments for accuracy, precision, recall and F1-score at each epoch, based on the source domain as HH109, target domain as HH101. Figure 7: Results of our method and comparison experiments for accuracy, precision, recall and F1-score at each epoch, based on the source domain as HH105, target domain as HH101. Figure 9: Results of our method and comparison experiments for accuracy, precision, recall and F1-score at each epoch, based on the source domain as HH105, target domain as HH110. Figure 11: Results of our method and comparison experiments for accuracy, precision, recall and F1-score at each epoch, based on the source domain as HH109, target domain as HH105.