Table 1 Predictors, extracted from CBR data, ordered according to their significance for applied dimensionality reduction method.

Ord	Decision tree	Random forest	Gradient boosting	Logistic regression	LASSO	Expert selection (CBR_EXP)
Ord	Decision tree	Random forest	Gradient boosting	Logistic regression	LASSO	Initial	Num	Avg	Final
1	PTA_VSSR8	Koos	Koos	Koos	Koos	Koos	5	1.2	Koos
2	Koos	PTA_VSSR8	PTA_VSSR8	Size	PTA_HSR8	SRT	5	3.8	SRT
3	PTA_DAR4	SRT	PTA_HSR8	SRT	Size	PTA_VSSR8	4	3.3	PTA_VSSR8
4	SRT	PTA_VSAR4	SRT	PTA_VS0.25	PTA_VSSR4	PTA_HSR8	4	4.0	PTA_HSR8
5	PTA_HSR8	PTA_VS3	Size	PTA_H8	SRT	Size	4	5.0	-
6	PTA_VSSR4	PTA_HSR8	PTA_VSIR8	PTA_H0.5	PTA_HIR8	PTA_VSSR4	3	5.7	-
7	PTA_DAR8	PTA_VSSR4	PTA_DAR4	PTA_H2	SDS	PTA_VS0.25	3	7.0	-
8	PTA_HIR8	PTA_VS0.25	PTA_DAR8	PTA_VS6	PTA_VSSR8	PTA_HIR8	3	7.7	-
9	PTA_VS3	MDL	PTA_HIR8	PTA_VS8	PTA_VS0.25	PTA_DAR4	2	5.0	PTA_DAR4
10	Size	PTA_H8	PTA_VS1	SDS	MDR	-	-	-	-

Irrelevant variables were rejected from expert selection. Variables and metrics are expressed as follows (see “Methods”): (a) suffix 4 holds for the basic frequency range, suffix 8 holds for the full frequency range; (b) subscripts H and VS hold for the healthy or diseased ear, respectively, subscript D holds for the difference of averaged PTA values between the two ears; (c) tailing abbreviations have the following meaning: AR average row wise, IR intercept row wise, SR slope row wise.

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