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Table 3 Balanced accuracy, Precision, and Recall, and F1 score for both malicious (Mal) and benign (Ben) accounts for supervised learning algorithms used in state of the art approaches where hyperparameters were reported

From: Detecting malicious accounts in permissionless blockchains using temporal graph properties

Reference Classifier Accuracy balanced Precision Recall F1 score MCC
Mal Ben Mal Ben Mal Ben Score
Ostapowicz and Zbikowski (2019) RandomForest 0.64 0.98 1.00 0.29 1.00 0.44 1.00 0.52
SVM*
XGBoost 0.85 0.97 1.00 0.7 1.00 0.91 1.00 0.81
Singh (2019) KNN 0.73 0.89 0.99 0.48 0.99 0.62 0.99 0.64
  1. Here, we use 59 features and both EOA and SC dataset configuration. Here, we also report the Matthews Correlation Coefficient (MCC) score
  2. *Did not converge as the dataset was large