Time Series Classification On Pendigits
Metriken
Accuracy
NLL
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy | NLL | Paper Title | Repository |
|---|---|---|---|---|
| GP-Sig-LSTM | 0.928 | 0.289 | Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances | |
| GP-Sig-GRU | 0.902 | 0.399 | Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances | |
| SNLST | 0.954 | - | Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections | |
| GP-KConv1D | 0.946 | 0.181 | Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances | |
| GP-GRU | 0.951 | 0.187 | Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances | |
| GP-Sig | 0.955 | 0.146 | Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances | |
| FCN-SNLST | 0.953 | - | Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections | |
| GP-LSTM | 0.953 | 0.185 | Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances |
0 of 8 row(s) selected.