# Time Series Classification with Shapelet and Canonical Features
## 5 Experimental Analysis
### Parameter Settings
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Dataset** & **Accuracy** & **Dataset** & **Accuracy** & **Dataset** & **Accuracy** & **Dataset** & **Accuracy** & **Dataset** & **Accuracy** \\ \hline ACSF1 & 86.00 & ECG200 & 86.00 & **Hering** & 67.19 & PhoC & 82.52 & **Strwbe** & 96.76 \\
**Adaic** & 77.75 & ECG500 & 94.53 & House20 & 97.48 & Phoneme & 38.19 & **SwLefaf** & 95.20 \\
**ArrHead** & 81.71 & **ECG5D** & 100.00 & InIkka & 47.45 & PigAirP & 40.38 & **Symbolis** & 98.69 \\
**Beef** & 76.67 & ElecDev & 74.57 & InEPGKT & 100.00 & PigArtP & 97.60 & **SynCtl** & 99.33 \\
**BeetFly** & 85.00 & EOGHS & 65.47 & InEPGST & 100.00 & PigCVP & 60.58 & **ToseSeg1** & 96.93 \\
**BirdChi** & 90.00 & EOGVS & 56.63 & InWSDad & 65.35 & **Plane** & 100.00 & **ToseSeg2** & 89.23 \\
**BME** & 100.00 & EHLevel & 57.60 & **ItUpwDe** & 96.02 & **PowCons** & 99.44 & **Trace** & 100.00 \\
**Car** & 90.00 & FaceA & 76.51 & LKitApp & 80.00 & **PrPhOAG** & 82.93 & **TwLECG** & 99.82 \\
**CBF** & 100.00 & **FaceF** & 100.00 & Light2 & 77.05 & **PrPhOC** & 87.63 & TwPatt & 99.80 \\
**Chtown** & 97.38 & FacesU & 92.63 & **Light7** & 75.34 & **PrPhTW** & 80.49 & **UMD** & 97.22 \\ ChConc & 70.89 & **50 Words** & 78.68 & Mallat & 98.59 & RefDev & 58.13 & UWAsll & 97.54 \\ CinCECG & 93.70 & Fish & 97.14 & **Meat** & 93.33 & Rock & 86.00 & UWax & 82.72 \\
**Coffee** & 100.00 & FordA & 92.27 & **Mdlmg** & 74.87 & ScrType & 52.00 & UWaY & 76.33 \\ Comput & 72.80 & FordB & 77.90 & **MdpHOAG** & 62.99 & SeHGCh2 & 94.50 & UWaZ & 77.44 \\
**Cricket** & 76.67 & FreeRT & 100.00 & **MdpHOC** & 83.16 & SeHHCMc2 & 88.89 & Wafer & 99.74 \\
**CricketY** & 81.54 & FreeST & 99.93 & **MdpThTW** & 58.44 & SeHGCh2 & 93.56 & **Wine** & 70.37 \\
**CricketZ** & 83.08 & **GunP** & 99.33 & MixSRT & 95.75 & ShpSim & 98.33 & **WordSyn** & 70.53 \\ Crop & 77.00 & **GunPAS** & 99.05 & MixSST & 94.14 & **ShpAll** & 85.67 & Worms & 75.32 \\
**DiaSked** & 85.29 & **GunPMF** & 99.68 & **MStF** & 93.37 & SKitApp & 81.87 & WormsTC & 79.22 \\
**DiPhOAG** & 74.82 & **GunPOY** & 100.00 & NoEGCT1 & 93.18 & **SmithSub** & 98.67 & Yoga & 89.47 \\
**DiPhWC** & 78.26 & **Ham** & 76.19 & NoEGCT2 & 94.71 & **SonyRS1** & 83.19 & \\
**DiPhTW** & 69.06 & HandOut & 92.70 & **OliOil** & 83.33 & **SonyRS2** & 85.73 & \\
**Earthqu** & 74.82 & Haptics & 53.57 & **OSULeaf** & 75.62 & StarCur & 98.13 & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Accuracy of RSFCF on 112 UCR time series datasets (%). As shown in Figure 4, the accuracy of RSFCF increases with the size of ensemble. Although the average accuracy tends to stabilize when the number of trees exceeds 100, it can be seen from the box diagram in Figure 4 that the accuracy rate of RSFCF in 10 experiments at \(r=500\) is more stable than at \(r=100\). The efficiency comparison analysis in the next section shows that RSFCF can still maintain a significant advantage in efficiency when \(r\) is set to 500, and when there is a higher requirement for efficiency, setting \(r\) to 100 can achieve a five-fold efficiency improvement without causing a significant reduction in classification accuracy. **Effect of the number of features used in data transformation \(a\) on the performance of RSFCF** (\(r\) set to 500, _shift_ is set to \(1/10\)). Figure 5 shows how the average accuracy of RSFCF on the Small60 dataset compares to the average training time at different settings of parameter \(a\). As the value of parameter \(a\) increases, the average accuracy generally shows an upward trend, and the average training time also increases (nearly linear). Since the design goal of RSFCF is to achieve accurate and efficient time series classification, we set \(a\) to 8, which loses only a small amount of accuracy but achieves nearly twice the efficiency improvement compared to using all features (i.e., setting \(a\) to 25). **Effect of the maximum offset of Shapelet _shift_ on the performance of RSFCF** (\(r\) set to 500, \(a\) is set to 8). Parameter _shift_ is set to restrict the scope of the Shapelet matching process.