TreeEnsembleClassifier - 1 vs 3

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1. TreeEnsembleClassifier1 → TreeEnsembleClassifier3 +19 -1

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1	- Tree Ensemble classifier. Returns the top class for each of N inputs.<br>
1	+ Tree Ensemble classifier. Returns the top class for each of N inputs.<br>
2 2	The attributes named 'nodes_X' form a sequence of tuples, associated by
3 3	index into the sequences, which must all be of equal length. These tuples
4 4	define the nodes.<br>
5 5	Similarly, all fields prefixed with 'class_' are tuples of votes at the leaves.
6 6	A leaf may have multiple votes, where each vote is weighted by
7 7	the associated class_weights index.<br>
8 8	One and only one of classlabels_strings or classlabels_int64s
9 9	will be defined. The class_ids are indices into this list.
10	+ All fields ending with <i>_as_tensor</i> can be used instead of the
11	+ same parameter without the suffix if the element type is double and not float.
10 12	### Attributes
11 13	* **base_values - FLOATS** :
14	+
15	+ 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)
16	+
17	+ * **base_values_as_tensor - TENSOR** :
12 18	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)
13 19	* **class_ids - INTS** :
14 20	The index of the class list that each weight is for.
15 21	* **class_nodeids - INTS** :
16 22	node id that this weight is for.
17 23	* **class_treeids - INTS** :
18 24	The id of the tree that this node is in.
19 25	* **class_weights - FLOATS** :
26	+
27	+ The weight for the class in class_id.
28	+
29	+ * **class_weights_as_tensor - TENSOR** :
20 30	The weight for the class in class_id.
21 31	* **classlabels_int64s - INTS** :
22 32	Class labels if using integer labels.<br>One and only one of the 'classlabels_*' attributes must be defined.
23 33	* **classlabels_strings - STRINGS** :
24 34	Class labels if using string labels.<br>One and only one of the 'classlabels_*' attributes must be defined.
25 35	* **nodes_falsenodeids - INTS** :
26 36	Child node if expression is false.
27 37	* **nodes_featureids - INTS** :
28 38	Feature id for each node.
29 39	* **nodes_hitrates - FLOATS** :
40	+
41	+ Popularity of each node, used for performance and may be omitted.
42	+
43	+ * **nodes_hitrates_as_tensor - TENSOR** :
30 44	Popularity of each node, used for performance and may be omitted.
31 45	* **nodes_missing_value_tracks_true - INTS** :
32 46	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.
33 47	* **nodes_modes - STRINGS** :
34 48	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'
35 49	* **nodes_nodeids - INTS** :
36 50	Node id for each node. Ids may restart at zero for each tree, but it not required to.
37 51	* **nodes_treeids - INTS** :
38 52	Tree id for each node.
39 53	* **nodes_truenodeids - INTS** :
40 54	Child node if expression is true.
41 55	* **nodes_values - FLOATS** :
56	+
57	+ Thresholds to do the splitting on for each node.
58	+
59	+ * **nodes_values_as_tensor - TENSOR** :
42 60	Thresholds to do the splitting on for each node.
43 61	* **post_transform - STRING** (default is 'NONE'):
44 62	Indicates the transform to apply to the score. <br> One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT.'
45 63	### Inputs
46 64	- **X** (heterogeneous) - **T1**:
47 65	Input of shape [N,F]
48 66	### Outputs
49 67	- **Y** (heterogeneous) - **T2**:
50 68	N, Top class for each point
51 69	- **Z** (heterogeneous) - **tensor(float)**:
52 70	The class score for each class, for each point, a tensor of shape [N,E].
53 71	### Type Constraints
54 72	* **T1** in ( tensor(double), tensor(float), tensor(int32), tensor(int64) ):
55 73	The input type must be a tensor of a numeric type.
56 74	* **T2** in ( tensor(int64), tensor(string) ):
57 75	The output type will be a tensor of strings or integers, depending on which of the classlabels_* attributes is used.