Time Series Classification on PENDIGITS (test) using Accuracy
97AccuracyMLSTMFCN
Evaluation Results
| Method | Links | |
|---|---|---|
| MLSTMFCN2019.06 | 97 | |
| MLSTMFCN2020.06 | 97 | |
| FCN128Backbone=FCN, Filter size=1282020.06 | 96.7 | |
| RESNETBackbone=ResNet2020.06 | 96.3 | |
| FCN64-LS2T64Backbone=FCN, Backbone Filter size=64, Rank=642020.06 | 96.3 | |
| FCN128-LS2T64Backbone=FCN, Backbone Filter size=128, Rank=642020.06 | 96.2 | |
| Baseline end-to-endm (number of modalities)=1, dm (number of variates)=2, Tm (sequence length)=8, C (number of classes)=10, Train size=7494, Test size=34982026.03 | 96.2 | |
| Baseline stagedm (number of modalities)=1, dm (number of variates)=2, Tm (sequence length)=8, C (number of classes)=10, Train size=7494, Test size=34982026.03 | 95.7 | |
| LLM NASm (number of modalities)=1, dm (number of variates)=2, Tm (sequence length)=8, C (number of classes)=10, Train size=7494, Test size=3498, NAS search budget (cycles)=102026.03 | 95.7 | |
| LS2T64Rank=642020.06 | 95.6 | |
| GP-SIG2019.06 | 95.5 | |
| GP-LSTM2019.06 | 95.3 | |
| ARKernel2019.06 | 95.2 | |
| ARKERNEL2020.06 | 95.2 | |
| GP-GRU2019.06 | 95.1 | |
| GP-KCONV1D2019.06 | 94.6 | |
| GRSF2019.06 | 93.2 | |
| gRSF2020.06 | 93.2 | |
| GP-SIG-LSTM2019.06 | 92.8 | |
| DTW2019.06 | 92.7 | |
| DTW2020.06 | 92.7 | |
| mVARF2019.06 | 92.3 | |
| mvARF2020.06 | 92.3 | |
| SMTS2019.06 | 91.7 | |
| SMTS2020.06 | 91.7 | |
| MUSE2019.06 | 91.2 | |
| MUSE2020.06 | 91.2 | |
| LPS2019.06 | 90.8 | |
| LPS2020.06 | 90.8 | |
| GP-SIG-GRU2019.06 | 90.2 | |
| Previous workm (number of modalities)=1, dm (number of variates)=2, Tm (sequence length)=8, C (number of classes)=10, Train size=7494, Test size=34982026.03 | 87.5 | |
| MCLModel=Linear, Trials=10, Presence of unlabeled samples=false, #n=10092, #f=16, #c=102020.01 | 84.32 | |
| FwdModel=Linear, Trials=10, Presence of unlabeled samples=false, #n=10092, #f=16, #c=102020.01 | 77.91 | |
| PCModel=Linear, Trials=10, Presence of unlabeled samples=false, #n=10092, #f=16, #c=102020.01 | 62.98 | |
| MCULModel=Linear, Trials=10, Presence of unlabeled samples=true, #n=10092, #f=16, #c=102020.01 | 28.03 | |
| GAModel=Linear, Trials=10, Presence of unlabeled samples=false, #n=10092, #f=16, #c=102020.01 | 15.01 | |
| MCLModel=Linear, Trials=10, Presence of unlabeled samples=true, #n=10092, #f=16, #c=102020.01 | 11.44 | |
| GAModel=Linear, Trials=10, Presence of unlabeled samples=true, #n=10092, #f=16, #c=102020.01 | 11.05 | |
| FwdModel=Linear, Trials=10, Presence of unlabeled samples=true, #n=10092, #f=16, #c=102020.01 | 8.09 | |
| PCModel=Linear, Trials=10, Presence of unlabeled samples=true, #n=10092, #f=16, #c=102020.01 | 5.98 |