# Weighted \(z\)-Distance-Based Clustering and Its Application to Time-Series Data
## 4 Experimental Results
### Time-Series Datasets
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Dataset** & **Gmm** & **SCC** & **SCC-I** & **SCC-I** \\ \hline \multirow{4}{*}{CBF} & Fscore & 0.6101/7 & 0.5822/8 & 0.6694/4 & **0.8032/1** \\  & RI & 0.6770/7 & 0.5925/8 & 0.7192/3 & **0.7516/1** \\  & NMI & 0.3559/6 & 0.2837/8 & 0.4302/4 & **0.4860/1** \\  & Time(s) & 0.470 & 0.040 & 1.040 & 1.200 \\ \hline \multirow{4}{*}{Coffee} & Fscore & 0.7366/7 & 0.6849/8 & 0.7619/4 & 0.7745/3 \\  & RI & 0.6358/6 & 0.5331/8 & 0.6295/7 & 0.6451/5 \\  & NMI & 0.2649/7 & 0.1329/8 & 0.3109/5 & 0.3318/3 \\  & Time(s) & 0.070 & **0.003** & 0.020 & 0.120 \\ \hline \multirow{4}{*}{ECG5} & Fscore & 0.5438/4 & 0.5321/5 & 0.5178/6 & **0.7395/1** \\  & RI & 0.5013/4 & 0.5003/5 & 0.5001/6 & **0.6147/1** \\  & NMI & 0.0029/4 & 0.0014/5 & 0.0009/6 & **0.1750/1** \\  & Time(s) & 0.040 & 0.040 & 0.430 & 1.600 \\ \hline \multirow{4}{*}{Face4} & Fscore & 0.6136/6 & 0.6107/7 & 0.7008/3 & **0.8185/1** \\  & RI & 0.7065/6 & 0.6339/8 & 0.7470/3 & **0.8655/1** \\  & NMI & 0.4220/6 & 0.3846/7 & 0.5163/3 & **0.7540/1** \\  & Time(s) & 0.090 & **0.007** & 0.060 & 0.540 \\ \hline \multirow{4}{*}{Light7} & Fscore & 0.4967/7 & 0.5082/6 & 0.5819/2 & **0.6036/1** \\  & RI & 0.7783/6 & 0.692/7 & 0.8033/3 & 0.7809/5 \\  & NMI & 0.4110/6 & 0.3985/7 & 0.4985/3 & **0.5048/1** \\  & Time(s) & 0.130 & **0.010** & 0.100 & 0.680 \\ \hline \multirow{4}{*}{Oil} & Fscore & 0.8103/6 & 0.6979/8 & 0.7728/7 & **0.8671/1** \\  & RI & 0.8548/4 & 0.6984/8 & 0.8042/7 & **0.8823/1** \\  & NMI & 0.6579/6 & 0.5155/8 & 0.6250/7 & **0.7422/1** \\  & Time(s) & 2.400 & **0.004** & 0.030 & 0.650 \\ \hline \multirow{4}{*}{OSU\_leaf} & Fscore & 0.3606/7 & 0.3612/6 & **0.4295/1** & 0.4252/2 \\  & RI & 0.7086/6 & 0.5978/7 & 0.7265/5 & 0.7350/4 \\  & NMI & 0.1663/6 & 0.1636/7 & **0.2562/1** & 0.2398/2 \\  & Time(s) & 0.36 & **0.030** & 0.700 & 2.200 \\ \hline \multirow{4}{*}{Sony\_Surf} & Fscore & 0.6604/8 & 0.6869/7 & 0.8033/3 & 0.8361/2 \\  & RI & 0.5627/7 & 0.5335/8 & 0.6838/5 & 0.7275/2 \\  & NMI & 0.1569/7 & 0.0814/8 & 0.3432/5 & 0.4245/2 \\  & Time(s) & 0.020 & 0.030 & 0.320 & 0.410 \\ \hline \multirow{4}{*}{Synthetic} & Fscore & 0.5924/7 & 0.6789/5 & 0.5524/8 & 0.7164/4 \\  & RI & 0.8128/7 & 0.8588/5 & 0.7175/8 & 0.8694/4 \\  & NMI & 0.6378/7 & 0.7703/5 & 0.6161/8 & 0.7932/2 \\  & Time(s) & 1.000 & 0.290 & 0.030 & 0.450 \\ \hline \multirow{4}{*}{Trace} & Fscore & 0.5500/7 & 0.6128/3 & 0.5896/4 & **0.7622/1** \\  & RI & 0.7500/5 & 0.7506/4 & 0.7514/3 & **0.8313/1** \\ \cline{1-1}  & NMI & 0.5188/6 & 0.5696/3 & 0.5452/4 & **0.7649/1** \\ \cline{1-1}  & Time(s) & 0.300 & 0.010 & 0.100 & 0.620 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Performance comparisons of Fscore, RI, and NMI on 10 time-series datasets—Part II. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**K-Means**} & \multicolumn{2}{c}{**TSKmeans**} & \multicolumn{2}{c}{**DSKmeans**} & \multicolumn{2}{c}{**FCM**} \\ \hline Fscore & 4.6 & 3.6 & 3.6 & 5.4 \\ RI & 3.6 & 3.4 & 4.1 & 4.8 \\ NMI & 3.9 & 4.0 & 3.7 & 5.5 \\ \hline \multirow{3}{*}{Fscore} & **Gmm** & **SCC** & **SCC-I** & **SCC-IW** \\  & 6.6 & 6.3 & 4.2 & **1.7** \\ RI & 5.8 & 6.8 & 5.0 & **2.5** \\ NMI & 6.1 & 6.6 & 4.6 & **1.5** \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Pairwise comparisons by \(t\)-test for time series datasets.