TreeNode
01 Syntax
Microsoft.VisualBasic.MachineLearning.XGBoost.train.TreeNode
02 Methods
| Name | Overloads | Summary |
|---|---|---|
| clean_up | 1 | release memory |
| Grad_add | 1 | |
| Hess_add | 1 | |
| num_sample_add | 1 | |
| Grad_setter | 1 | |
| Hess_setter | 1 | |
| update_best_split | 1 | |
| set_categorical_feature_best_split | 1 | |
| get_best_feature_threshold_gain | 1 | |
| internal_node_setter | 1 | |
| leaf_node_setter | 1 |
03 Fields
| Name | Overloads | Summary |
|---|---|---|
| index | 1 | |
| depth | 1 | |
| feature_dim | 1 | |
| is_leaf | 1 | |
| num_sample | 1 | |
| Grad | 1 | |
| Hess | 1 | |
| G_left | 1 | |
| H_left | 1 | |
| nan_go_to | 1 | |
| Grad_missing | 1 | |
| Hess_missing | 1 | |
| split_feature | 1 | |
| split_threshold | 1 | |
| split_left_child_catvalue | 1 | |
| nan_child | 1 | |
| left_child | 1 | |
| right_child | 1 | |
| cat_feature_col_value_GH | 1 |
04 Members
clean_up
release memory
index
depth
feature_dim
is_leaf
num_sample
Grad
Hess
G_left
H_left
nan_go_to
Grad_missing
Hess_missing
split_feature
split_threshold
split_left_child_catvalue
nan_child
left_child
right_child
cat_feature_col_value_GH
Grad_add(
Double)Hess_add(
Double)num_sample_add(
Double)Grad_setter(
Double)Hess_setter(
Double)update_best_split(
Int32, Double, Double, Double)set_categorical_feature_best_split(
Int32, List(Of Int32), Double, Double)get_best_feature_threshold_gain()
leaf_node_setter(
Double, Boolean)