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

Table 2 Parameter Settings

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

ISSN: 1756-0381