Table 1 Comparison of performance of various classifiers to develop screening model in the training dataset.

From: Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach

Classifier name

Correctly classified instances % (value)

Kappa statistic

Mean absolute error

Root mean square error

MCC

ROC

J48

93.18

0.62

0.06

0.23

0.634

0.951

Random forest

88.63

0.38

0.13

0.28

0.385

0.874

LMT

90.9

0.45

0.16

0.3

0.471

0.795

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