Table 1.

Accuracy of models trained with various feature parameters added into AAC by 6-fold cross-validation.

Feature parameters added into AAC	Feature selection method	Added number of features/total number of features	Accuracy
CTD-C [10]	mRMR	20/39	75.1547%
CTriad [101]	mRMR	30/343	71.0349%
DPC [28]	ANOVA	30/400	75.5569%
DDE [28]	ANOVA	30/400	67.0483%
TPC [26]	ANOVA	30/8000	75.5569%
PseAAC [33]	ANOVA	30/50	73.5075%
Geary [30]	mRMR	30/240	75.8706%
CKSAAP (k = 0~5)	ANOVA	30/2400	75.9282%
CKSAAP (k = 0)	ANOVA	30/400	75.7776%
CKSAAP (k = 1)	ANOVA	30/400	76.0885%
CKSAAP (k = 2)	ANOVA	30/400	75.7147%
CKSAAP (k = 3)	ANOVA	30/400	76.0878%
CKSAAP (k = 4)	ANOVA	30/400	75.8708%
CKSAAP (k = 5)	ANOVA	30/400	75.8701%