Table 1.

Hyperparameters for LightGBM model optimization.

Hyperparameters	Meaning
learning_rate	Learning rate
min_child_samples	Minimum number of samples required for leaf nodes
max_depth	Maximum depth
num_leaves	Number of leaf nodes in each tree
max_bin	Maximum possible number of eigenvalue bins
min_data_in_leaf	Minimum number of samples for leaf nodes
feature_fraction	Proportion of feature subsets used to train the model
bagging_fraction	Control the sampling ratio of the training data
bagging_freq	Frequency of bagging
reg_alpha	L1 regular term coefficient
reg_lambda	L2 regular term coefficient