Table 4.

Trainable parameters of the assembled final classification pipeline.

Parameter	Value
minmax_rescaler__clip	False
minmax_rescaler__copy	True
minmax_rescaler__feature_range	(0, 1)
linear_svm_classifier__C	0.10284379327993369
linear_svm_classifier__class_weight	None
linear_svm_classifier__dual	False
linear_svm_classifier__fit_intercept	True
linear_svm_classifier__intercept_scaling	1
linear_svm_classifier__loss	squared_hinge
linear_svm_classifier__max_iter	1,000
linear_svm_classifier__multi_class	‘ovr’
linear_svm_classifier__penalty	‘l2’
linear_svm_classifier__random_state	42
linear_svm_classifier__tol	0.0001

All the trainable model parameters for the classification algorithms are listed below to complete reproducibility of this study.