Table 6.

Learned hyperparameters of Auto-HMM-LMF method based on GDSC dataset

Hyperparameter	Description	Value
k	Number of nearest neighbors (Eq. 9)	20
α	Effectiveness of cell line similarity (Eq. 11)	0.5
β	Effectiveness of drug similarity (Eq. 11)	0.1
λc	Variance parameter of cell lines (Eq. 11)	0.5
λd	Variance parameter of drugs (Eq. 11)	0.5
λ	Importance of SimEXP (Eq. 8)	2
γ	Importance of SimCNV (Eq. 8)	2
ϕ	Importance of SimMUT (Eq. 8)	2
ψ	Importance of SimIC50 (Eq. 8)	5
ρ	Importance of SimTISSUE (Eq. 8)	2
threshold	Threshold parameter	0.4

The parameter k were selected from 1 to 50. The impact factors of nearest neighbors α and β in equations were selected from {2^–5, 2^–4, …, 2²}. The variance parameters, λ_c and λ_d, were chosen from {2^–5, 2^–4, …, 2¹}. The five parameters γ, λ, ϕ, ψ, and ρ were selected from 1 to 5