Ahmadi et al. (2016): API feature vector + XGBoost

Reported on 2 benchmarks across 1 task

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

Miscellaneous2 results

Malware ClassificationonMicrosoft Malware Classification Challenge
Accuracy (10-fold)
0.9868
best: 9641 (MalConv)
Malware ClassificationonMicrosoft Malware Classification Challenge
Macro F1 (10-fold)
0.9638
best: 0.9951 (HYDRA)