TreeEnsembleClassifier - 1 vs 5

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1. TreeEnsembleClassifier1 → TreeEnsembleClassifier5 +22 -1

TreeEnsembleClassifier1 → TreeEnsembleClassifier5 RENAMED Viewed

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1	+ This operator is DEPRECATED. Please use TreeEnsemble with provides similar functionality.
2	+ In order to determine the top class, the ArgMax node can be applied to the output of TreeEnsemble.
3	+ To encode class labels, use a LabelEncoder operator.
1	- Tree Ensemble classifier. Returns the top class for each of N inputs.<br>
4	+ Tree Ensemble classifier. Returns the top class for each of N inputs.<br>
2 5	The attributes named 'nodes_X' form a sequence of tuples, associated by
3 6	index into the sequences, which must all be of equal length. These tuples
4 7	define the nodes.<br>
5 8	Similarly, all fields prefixed with 'class_' are tuples of votes at the leaves.
6 9	A leaf may have multiple votes, where each vote is weighted by
7 10	the associated class_weights index.<br>
8 11	One and only one of classlabels_strings or classlabels_int64s
9 12	will be defined. The class_ids are indices into this list.
13	+ All fields ending with <i>_as_tensor</i> can be used instead of the
14	+ same parameter without the suffix if the element type is double and not float.
10 15	### Attributes
11 16	* **base_values - FLOATS** :
17	+
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)
19	+
20	+ * **base_values_as_tensor - TENSOR** :
12 21	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 22	* **class_ids - INTS** :
14 23	The index of the class list that each weight is for.
15 24	* **class_nodeids - INTS** :
16 25	node id that this weight is for.
17 26	* **class_treeids - INTS** :
18 27	The id of the tree that this node is in.
19 28	* **class_weights - FLOATS** :
29	+
30	+ The weight for the class in class_id.
31	+
32	+ * **class_weights_as_tensor - TENSOR** :
20 33	The weight for the class in class_id.
21 34	* **classlabels_int64s - INTS** :
22 35	Class labels if using integer labels.<br>One and only one of the 'classlabels_*' attributes must be defined.
23 36	* **classlabels_strings - STRINGS** :
24 37	Class labels if using string labels.<br>One and only one of the 'classlabels_*' attributes must be defined.
25 38	* **nodes_falsenodeids - INTS** :
26 39	Child node if expression is false.
27 40	* **nodes_featureids - INTS** :
28 41	Feature id for each node.
29 42	* **nodes_hitrates - FLOATS** :
43	+
44	+ Popularity of each node, used for performance and may be omitted.
45	+
46	+ * **nodes_hitrates_as_tensor - TENSOR** :
30 47	Popularity of each node, used for performance and may be omitted.
31 48	* **nodes_missing_value_tracks_true - INTS** :
32 49	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 50	* **nodes_modes - STRINGS** :
34 51	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 52	* **nodes_nodeids - INTS** :
36 53	Node id for each node. Ids may restart at zero for each tree, but it not required to.
37 54	* **nodes_treeids - INTS** :
38 55	Tree id for each node.
39 56	* **nodes_truenodeids - INTS** :
40 57	Child node if expression is true.
41 58	* **nodes_values - FLOATS** :
59	+
60	+ Thresholds to do the splitting on for each node.
61	+
62	+ * **nodes_values_as_tensor - TENSOR** :
42 63	Thresholds to do the splitting on for each node.
43 64	* **post_transform - STRING** (default is 'NONE'):
44 65	Indicates the transform to apply to the score. <br> One of 'NONE,' 'SOFTMAX,' 'LOGISTIC,' 'SOFTMAX_ZERO,' or 'PROBIT.'
45 66	### Inputs
46 67	- **X** (heterogeneous) - **T1**:
47 68	Input of shape [N,F]
48 69	### Outputs
49 70	- **Y** (heterogeneous) - **T2**:
50 71	N, Top class for each point
51 72	- **Z** (heterogeneous) - **tensor(float)**:
52 73	The class score for each class, for each point, a tensor of shape [N,E].
53 74	### Type Constraints
54 75	* **T1** in ( tensor(double), tensor(float), tensor(int32), tensor(int64) ):
55 76	The input type must be a tensor of a numeric type.
56 77	* **T2** in ( tensor(int64), tensor(string) ):
57 78	The output type will be a tensor of strings or integers, depending on which of the classlabels_* attributes is used.