Skip to main content

Table 2 Parameter Settings

From: LPI-EnEDT: an ensemble framework with extra tree and decision tree classifiers for imbalanced lncRNA-protein interaction data classification

Method Parameter setting
LPI-BLS s=1, c= 10−10, N1=3, N2=60, N3=900
LPI-CastBoost learning_rate=0.5, loss_function=’Logloss’
  logging_level=’Verbose’
PLIPCOM learning_rate=0.01,n_estimators=100
  min_samples_split=2, max_depth=3
LPI-EnEDT n_estimators=10, depth=5, split=5, neighbours=3