Trees#
Digging into the tree structure#
mlinsights.mltree.predict_leaves
(model, X)
Returns the leave every observations of X falls into.
mlinsights.mltree.tree_structure.tree_find_common_node
(tree, i, j, parents = None)
Finds the common node to nodes i and j.
mlinsights.mltree.tree_structure.tree_find_path_to_root
(tree, i, parents = None)
Lists nodes involved into the path to find node i.
mlinsights.mltree.tree_structure.tree_node_parents
(tree)
Returns a dictionary
{node_id: parent_id}
.
mlinsights.mltree.tree_node_range
(tree, i, parents = None)
Determines the ranges for a node all dimensions.
nan
means infinity.
mlinsights.mltree.tree_leave_index
(model)
Returns the indices of every leave in a tree.
mlinsights.mltree.tree_leave_neighbors
(model)
The function determines which leaves are neighbors. The method uses some memory as it creates creates a grid of the feature spaces, each split multiplies the number of cells by two.
Experiments, exercise#
mlinsights.mltree.digitize2tree
(bins, right = False)
Builds a decision tree which returns the same result as lambda x: numpy.digitize(x, bins, right=right) (see numpy.digitize).