TreeEnsembleRegressor#

  • 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

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: no

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#