PWGK

Reported on 6 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Graphs3 results

Graph ClassificationonNEURON-MULTI
Accuracy· 2017-06-12
45.5
best: 69.1 (WKPI-kcenters)
Kernel method for persistence diagrams via kernel embedding and weight factor arXiv:1706.03472
Graph ClassificationonNEURON-BINARY
Accuracy· 2017-06-12
80.1
best: 90.3 (WKPI-kmeans)
Kernel method for persistence diagrams via kernel embedding and weight factor arXiv:1706.03472
Graph ClassificationonNEURON-Average
Accuracy· 2017-06-12
62.8
best: 77.8 (WKPI-kcenters)
Kernel method for persistence diagrams via kernel embedding and weight factor arXiv:1706.03472

Methodology3 results

ClassificationonNEURON-MULTI
Accuracy· 2017-06-12
45.5
best: 69.1 (WKPI-kcenters)
Kernel method for persistence diagrams via kernel embedding and weight factor arXiv:1706.03472
ClassificationonNEURON-BINARY
Accuracy· 2017-06-12
80.1
best: 90.3 (WKPI-kmeans)
Kernel method for persistence diagrams via kernel embedding and weight factor arXiv:1706.03472
ClassificationonNEURON-Average
Accuracy· 2017-06-12
62.8
best: 77.8 (WKPI-kcenters)
Kernel method for persistence diagrams via kernel embedding and weight factor arXiv:1706.03472