.. _l-onnx-opai-onnx-ml-treeensembleclassifier-d3-5:

TreeEnsembleClassifier - 3 vs 5
===============================

Next section compares an older to a newer version of the same operator 
after both definition are converted into markdown text.
Green means an addition to the newer version, red means a deletion.
Anything else is unchanged.

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    --- a/TreeEnsembleClassifier3
    +++ b/TreeEnsembleClassifier5
    @@ -1 +1 @@
    + This operator is DEPRECATED. Please use TreeEnsemble with provides similar functionality.
    + In order to determine the top class, the ArgMax node can be applied to the output of TreeEnsemble.
    + To encode class labels, use a LabelEncoder operator.
      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>
      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.<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.
  
      ### Attributes
  
      * **base_values - FLOATS** :
  
        Base values for classification, added to final class score; the size must be the same as the classes or can be left unassigned (assumed 0)
  
      * **base_values_as_tensor - TENSOR** :
  
        Base values for classification, added to final class score; the size must be the same as the classes or can be left unassigned (assumed 0)
  
      * **class_ids - INTS** :
  
        The index of the class list that each weight is for.
  
      * **class_nodeids - INTS** :
  
        node id that this weight is for.
  
      * **class_treeids - INTS** :
  
        The id of the tree that this node is in.
  
      * **class_weights - FLOATS** :
  
        The weight for the class in class_id.
  
      * **class_weights_as_tensor - TENSOR** :
  
        The weight for the class in class_id.
  
      * **classlabels_int64s - INTS** :
  
        Class labels if using integer labels.<br>One and only one of the 'classlabels_*' attributes must be defined.
  
      * **classlabels_strings - STRINGS** :
  
        Class labels if using string labels.<br>One and only one of the 'classlabels_*' attributes must be defined.
  
      * **nodes_falsenodeids - INTS** :
  
        Child node if expression is false.
  
      * **nodes_featureids - INTS** :
  
        Feature id for each node.
  
      * **nodes_hitrates - FLOATS** :
  
        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 - INTS** :
  
        For each node, define what to do in the presence of a missing value: if a value is missing (NaN), use the 'true' or 'false' branch based on the value in this array.<br>This attribute may be left undefined, and the default value is false (0) for all nodes.
  
      * **nodes_modes - STRINGS** :
  
        The node kind, that is, the comparison to make at the node. There is no comparison to make at a leaf node.<br>One of 'BRANCH_LEQ', 'BRANCH_LT', 'BRANCH_GTE', 'BRANCH_GT', 'BRANCH_EQ', 'BRANCH_NEQ', 'LEAF'
  
      * **nodes_nodeids - INTS** :
  
        Node id for each node. Ids may restart at zero for each tree, but it not required to.
  
      * **nodes_treeids - INTS** :
  
        Tree id for each node.
  
      * **nodes_truenodeids - INTS** :
  
        Child node if expression is true.
  
      * **nodes_values - FLOATS** :
  
        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** (default is 'NONE'):
  
        Indicates the transform to apply to the score. <br> One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT.'
  
      ### Inputs
  
      - **X** (heterogeneous) - **T1**:
  
        Input of shape [N,F]
  
      ### Outputs
  
      - **Y** (heterogeneous) - **T2**:
  
        N, Top class for each point
      - **Z** (heterogeneous) - **tensor(float)**:
  
        The class score for each class, for each point, a tensor of shape [N,E].
  
      ### Type Constraints
  
      * **T1** in ( tensor(double), tensor(float), tensor(int32), tensor(int64) ):
  
        The input type must be a tensor of a numeric type.
      * **T2** in ( tensor(int64), tensor(string) ):
  
        The output type will be a tensor of strings or integers, depending on which of the classlabels_* attributes is used.
    `;

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