TreeEnsembleRegressor#

Warning

This operator is deprecated.

  • Domain: ai.onnx.ml

  • Since version: 5

This operator is DEPRECATED. Please use TreeEnsemble instead which provides the same functionality. Tree Ensemble regressor. Returns the regressed values for each input in N. All args with nodes are fields of a tuple of tree nodes, and it is assumed they are the same length, and an index i will decode the tuple across these inputs. Each node id can appear only once for each tree id. All fields prefixed with target are tuples of votes at the leaves. A leaf may have multiple votes, where each vote is weighted by the associated target_weights index. All fields ending with _as_tensor can be used instead of the same parameter without the suffix if the element type is double and not float. All trees must have their node ids start at 0 and increment by 1. Mode enum is BRANCH_LEQ, BRANCH_LT, BRANCH_GTE, BRANCH_GT, BRANCH_EQ, BRANCH_NEQ, LEAF

Inputs

  • X (T): Input of shape [N,F]

Outputs

  • Y (tensor(float)): N classes

Attributes

  • aggregate_function (string): Defines how to aggregate leaf values within a target.

  • base_values (float[]): Base values for regression, added to final prediction after applying aggregate_function.

  • base_values_as_tensor (tensor): Base values for regression, added to final prediction.

  • n_targets (int): The total number of targets.

  • nodes_falsenodeids (int[]): Child node if expression is false.

  • nodes_featureids (int[]): Feature id for each node.

  • nodes_hitrates (float[]): Popularity of each node, used for performance and may be omitted.

  • nodes_hitrates_as_tensor (tensor): Popularity of each node, used for performance and may be omitted.

  • nodes_missing_value_tracks_true (int[]): For each node, define what to do in the presence of a NaN.

  • nodes_modes (string[]): The node kind, that is, the comparison to make at the node.

  • nodes_nodeids (int[]): Node id for each node. Node ids must restart at zero for each tree and increase sequentially.

  • nodes_treeids (int[]): Tree id for each node.

  • nodes_truenodeids (int[]): Child node if expression is true.

  • nodes_values (float[]): Thresholds to do the splitting on for each node.

  • nodes_values_as_tensor (tensor): Thresholds to do the splitting on for each node.

  • post_transform (string): Indicates the transform to apply to the score.

  • target_ids (int[]): The index of the target that each weight is for.

  • target_nodeids (int[]): The node id of each weight.

  • target_treeids (int[]): The id of the tree that each node is in.

  • target_weights (float[]): The weight for each target.

  • target_weights_as_tensor (tensor): The weight for each target.

Type Constraints

  • T: The input type must be a tensor of a numeric type. Allowed types: tensor(double), tensor(float), tensor(int32), tensor(int64).

Differences with previous version (3)#

SchemaDiff: TreeEnsembleRegressor (domain 'ai.onnx.ml')

  • old version: 3

  • new version: 5

  • breaking: yes

Breaking reasons:

  • operator deprecated: False -> True

Deprecation:

  • [BREAKING] deprecated False -> True

Documentation:

  • line similarity: 0.93 (+2/-0 lines)

--- TreeEnsembleRegressor v3
+++ TreeEnsembleRegressor v5
@@ -1,4 +1,6 @@

+    This operator is DEPRECATED. Please use TreeEnsemble instead which provides the same
+    functionality.<br>
     Tree Ensemble regressor.  Returns the regressed values for each input in N.<br>
     All args with nodes_ are fields of a tuple of tree nodes, and
     it is assumed they are the same length, and an index i will decode the

Version History#