tree
version=v4
num_class=1
num_tree_per_iteration=1
label_index=0
max_feature_idx=1
objective=binary sigmoid:1
feature_names=num_feat cat_feat
feature_infos=[0:10] 0:1:2
tree_sizes=300

Tree=0
num_leaves=3
num_cat=1
split_feature=1 0
split_gain=150.5 80.2
threshold=0 5
decision_type=1 0
left_child=1 -1
right_child=-3 -2
leaf_value=0.3 -0.2 -0.4
leaf_weight=120 85 95
leaf_count=120 85 95
internal_value=0 0
internal_weight=300 205
internal_count=300 205
cat_boundaries=0 1
cat_threshold=3
is_linear=0
shrinkage=1

end of trees

feature_importances:
cat_feat=1
num_feat=1

parameters:
[boosting: gbdt]
[objective: binary]
[num_iterations: 1]
[learning_rate: 0.1]
[num_leaves: 31]
end of parameters

pandas_categorical:[[0, 1, 2]]