# Similarity Measurement and Classification of Temporal Data Based on Double Mean Representation
## 4 Experimental Validation
### Datasets  
The evaluation of SAX-DM's classification performance utilized the UCR Time Series Archive [28], which is a widely used collection of time series datasets in the field of time series data mining. This dataset was introduced in 2002 and has been continuously expanded over time. Due to its inclusion of time series datasets from various domains, it has become an important resource in the time series data mining community and is recommended by researchers working with time series data.  
Initially, the dataset contained only 16 datasets. However, since its introduction in 2002, it has been expanded, and it currently includes 128 datasets. These datasets cover seven different domains: Device, ECG, Image, Motion, Sensor, Simulated, and Spectro. After careful analysis and verification of the data, it was found that some datasets had missing values, with some missing data lengths exceeding half of their original data lengths. As the similarity measurement method based on the approximate expression in this paper relies on the concept of Euclidean distance and is applicable to equally sized time series data, it cannot calculate the similarity between time series data of unequal lengths. Therefore, some datasets were excluded from the analysis. In the end, this paper selected 100 datasets from the UCR Time Series Archive, covering the aforementioned seven domains, for the purpose of conducting time series data classification experiments. The list of datasets used can be found in Table 2.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Id** & **Type** & **Name** & **Train** & **Test** & **Class** & **Length** \\ \hline
1 & Device & ACSF1 & 100 & 100 & 10 & 1460 \\
2 & Image & Adiac & 390 & 391 & 37 & 176 \\
3 & Image & ArrowHead & 36 & 175 & 3 & 251 \\
4 & Spectro & Beef & 30 & 30 & 5 & 470 \\
5 & Image & BeefelFy & 20 & 20 & 2 & 512 \\
6 & Image & BirdChicken & 20 & 20 & 2 & 512 \\
7 & Simulated & BME & 30 & 150 & 3 & 128 \\
8 & Sensor & Car & 60 & 60 & 4 & 577 \\
9 & Simulated & CBF & 30 & 900 & 3 & 128 \\
10 & Traffic & Chintown & 20 & 343 & 2 & 24 \\
11 & Sensor & CinCECGToso & 40 & 1380 & 4 & 1639 \\
12 & Spectro & Coffee & 28 & 28 & 2 & 286 \\
13 & Device & Computers & 250 & 250 & 2 & 720 \\
14 & Motion & CricketX & 390 & 390 & 12 & 300 \\
15 & Motion & CricketY & 390 & 390 & 12 & 300 \\
16 & Motion & CricketZ & 390 & 390 & 12 & 300 \\
17 & Image & DatomSizeReduction & 16 & 306 & 4 & 345 \\
18 & Image & DistalPlanaxOutlineAgeGroup & 400 & 139 & 3 & 80 \\
19 & Image & DistalPlanaxOutlineCorrect & 600 & 276 & 2 & 80 \\
20 & Image & DistalPlanaxTW & 400 & 139 & 6 & 80 \\
21 & Sensor & Earthquakes & 322 & 139 & 2 & 512 \\
22 & ECG & ECG200 & 100 & 100 & 2 & 96 \\
23 & ECG & ECGFiveDays & 23 & 861 & 2 & 136 \\
24 & EOG & EOGHorizontalSignal & 362 & 362 & 12 & 1250 \\
25 & EOG & EOGVerticalSignal & 362 & 362 & 12 & 1250 \\
26 & Spectro & EthanolLevel & 504 & 500 & 4 & 1751 \\
27 & Image & FaceAll & 560 & 1690 & 14 & 131 \\
28 & Image & FaceFour & 24 & 88 & 4 & 350 \\
29 & Image & FacesUCR & 200 & 2050 & 14 & 131 \\
30 & Image & FiftyWords & 450 & 455 & 50 & 270 \\
31 & Image & Fish & 175 & 175 & 7 & 463 \\
32 & Sensor & FordA & 3601 & 1320 & 2 & 500 \\
33 & Sensor & FordB & 3636 & 810 & 2 & 500 \\
34 & HRM & Fungi & 18 & 186 & 18 & 201 \\
35 & Motion & GunPointPoint & 50 & 150 & 2 & 150 \\
36 & Motion & GunPointAgeSpan & 135 & 316 & 2 & 150 \\
37 & Motion & GunPointMaleVersiFemale & 135 & 316 & 2 & 150 \\
38 & Motion & GunPointOldversusYoung & 136 & 315 & 2 & 150 \\
39 & Spectro & Ham & 109 & 105 & 2 & 431 \\
40 & Image & HandOutlines & 1000 & 370 & 2 & 2709 \\ \hline \hline \end{tabular}
\end{table}
Table 2: List of time series datasets.