Table 5 Hyperparameters range for ECS TabNet.

From: Example dependent cost sensitive learning based selective deep ensemble model for customer credit scoring

Hyperparameter

Description

Value

\({N_a}\)

Attention layer dimension

{8, 16, 24, 32, 64}

\({N_d}\)

Decision layer dimension

{8, 16, 24, 32, 64}

\({N_{step}}\)

Number of decision steps

{3, 4, 5, 6},

\(gamma\)

Relaxation factor that controls the mask

{1.0, 1.2, 1.5, 2.0}

\(momentum\)

Control of the feature selection update process

{0.6, 0.7, 0.8, 0.9}