.. _op_ai_onnx_ml_TreeEnsembleRegressor-3:

TreeEnsembleRegressor - version 3
=================================

This page documents version **3** of operator **TreeEnsembleRegressor**. See :doc:`TreeEnsembleRegressor` for the latest version (since version 5).

- **Domain**: ``ai.onnx.ml``
- **Since version**: 3

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 (1)
-------------------------------------

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

* old version: 1
* new version: 3
* breaking: no

**Documentation:**

* line similarity: 0.92 (+2/-0 lines)

.. code-block:: diff

    --- TreeEnsembleRegressor v1
    +++ TreeEnsembleRegressor v3
    @@ -7,5 +7,7 @@
         All fields prefixed with target_ are tuples of votes at the leaves.<br>
         A leaf may have multiple votes, where each vote is weighted by
         the associated target_weights index.<br>
    +    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.
         All trees must have their node ids start at 0 and increment by 1.<br>
         Mode enum is BRANCH_LEQ, BRANCH_LT, BRANCH_GTE, BRANCH_GT, BRANCH_EQ, BRANCH_NEQ, LEAF