TreeEnsembleClassifier - version 3#
This page documents version 3 of operator TreeEnsembleClassifier. See TreeEnsembleClassifier for the latest version (since version 5).
Domain:
ai.onnx.mlSince version: 3
Tree Ensemble classifier. Returns the top class for each of N inputs.
The attributes named ‘nodes_X’ form a sequence of tuples, associated by
index into the sequences, which must all be of equal length. These tuples
define the nodes.
Similarly, all fields prefixed with class_ are tuples of votes at the leaves.
A leaf may have multiple votes, where each vote is weighted by
the associated class_weights index.
One and only one of classlabels_strings or classlabels_int64s
will be defined. The class_ids are indices into this list.
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.
Inputs
X (T1): Input of shape [N,F]
Outputs
Y (T2): N, Top class for each point
Z (tensor(float)): The class score for each class, for each point, a tensor of shape [N,E].
Attributes
base_values (float[]): Base values for classification, added to final class score.
base_values_as_tensor (tensor): Base values for classification, added to final class score.
class_ids (int[]): The index of the class list that each weight is for.
class_nodeids (int[]): node id that this weight is for.
class_treeids (int[]): The id of the tree that this node is in.
class_weights (float[]): The weight for the class in class_id.
class_weights_as_tensor (tensor): The weight for the class in class_id.
classlabels_int64s (int[]): Class labels if using integer labels. One and only one of the ‘classlabels*’ attributes must be defined.
classlabels_strings (string[]): Class labels if using string labels. One and only one of the ‘classlabels*’ attributes must be defined.
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 missing value.
nodes_modes (string[]): The node kind, that is, the comparison to make at the node.
nodes_nodeids (int[]): Node id for each node. Ids may restart at zero for each tree.
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.
Type Constraints
T1: The input type must be a tensor of a numeric type. Allowed types: tensor(double), tensor(float), tensor(int32), tensor(int64).
T2: The output type will be a tensor of strings or integers, depending on which of the classlabels* attributes is used. Allowed types: tensor(int64), tensor(string).
Differences with previous version (1)#
SchemaDiff: TreeEnsembleClassifier (domain 'ai.onnx.ml')
old version: 1
new version: 3
breaking: no
Attributes:
added ‘nodes_values_as_tensor’: type=TENSOR; required=False; default=UNDEFINED
added ‘nodes_hitrates_as_tensor’: type=TENSOR; required=False; default=UNDEFINED
added ‘class_weights_as_tensor’: type=TENSOR; required=False; default=UNDEFINED
added ‘base_values_as_tensor’: type=TENSOR; required=False; default=UNDEFINED
Documentation:
line similarity: 0.82 (+3/-1 lines)
--- TreeEnsembleClassifier v1
+++ TreeEnsembleClassifier v3
@@ -1,5 +1,5 @@
- Tree Ensemble classifier. Returns the top class for each of N inputs.<br>
+ Tree Ensemble classifier. Returns the top class for each of N inputs.<br>
The attributes named 'nodes_X' form a sequence of tuples, associated by
index into the sequences, which must all be of equal length. These tuples
define the nodes.<br>
@@ -8,3 +8,5 @@
the associated class_weights index.<br>
One and only one of classlabels_strings or classlabels_int64s
will be defined. The class_ids are indices into this list.
+ All fields ending with <i>_as_tensor</i> can be used instead of the
+ same parameter without the suffix if the element type is double and not float.