Перечисление MiningNodeType
Represents the type of the MiningContentNode.
Пространство имен: Microsoft.AnalysisServices.AdomdServer
Сборка: msmgdsrv (в msmgdsrv.dll)
Синтаксис
'Декларация
Public Enumeration MiningNodeType
'Применение
Dim instance As MiningNodeType
public enum MiningNodeType
public enum class MiningNodeType
type MiningNodeType
public enum MiningNodeType
Элементы
Имя элемента | Описание | |
---|---|---|
ArimaAutoRegressive | The node that contains the autoregressive coefficient for a single term in an ARIMA model. (29) | |
ArimaMovingAverage | The node that contains the moving average coefficient for a single term in an ARIMA model. (30) | |
ArimaPeriodicStructure | The node that represents a periodic structure in an ARIMA model. (28) | |
ArimaRoot | The root node of an ARIMA model. (27) | |
AssociationRule | The node represents an association rule detected by the algorithm. (8) | |
Cluster | The node represents a cluster detected by the algorithm. (5) | |
CustomBase | Represents the starting point for custom node types. Custom node types must be integers greater in value than this constant. This type is used by plug-in algorithms.
(1000) |
|
Distribution | The node represents the terminal node, or leaf node, of a classification tree. (4) | |
InputAttribute | The node corresponds to a predictable attribute. (10) | |
InputAttributeState | The node contains statistics about the states of an input attribute. (11) | |
Interior | The node represents an interior split node in a classification tree. (3) | |
ItemSet | The node represents an itemset detected by the algorithm. (7) | |
Model | The root content node. This node applies to all algorithms. (1) | |
NaiveBayesMarginalStatNode | The node containing marginal statistics about the training set, stored in a format used by the Naïve Bayes algorithm. (26) | |
NNetHiddenLayer | The node that groups together the nodes that describe the hidden layer. This type is used with neural network algorithms. (19) | |
NNetHiddenNode | The node is a node of the hidden layer. This type is used with neural network algorithms. (22) | |
NNetInputLayer | The node that groups together the nodes of the input layer. This type is used with neural network algorithms. (18) | |
NNetInputNode | The node is a node of the input layer. This node will usually match an input attribute and the corresponding states. This type is used with neural network algorithms. (21) | |
NNetMarginalNode | The node containing marginal statistics about the training set, stored in a format used by the algorithm. This type is used with neural network algorithms. (24) | |
NNetOutputLayer | The node that groups together the nodes of the output layer. This type is used with neural network algorithms. (21) | |
NNetOutputNode | The node is a node of the output layer. This node will usually match an output attribute and the corresponding states. This type is used with neural network algorithms. (23) | |
NNetSubnetwork | The node contains one sub-network. This type is used with neural network algorithms. (17) | |
PredictableAttribute | The node corresponds to a predictable attribute. (9) | |
RegressionTreeRoot | The node is the root of a regression tree. (25) | |
Sequence | The top node for a Markov model component of a sequence cluster. This node will have a node of type Cluster as a parent, and children of type Transition. (13) | |
TimeSeries | The non-root node of a time series tree. (15) | |
Transition | The node representing a row of a Markov transition matrix. This node will have a node of type Sequence as a parent, and no children. (14) | |
Tree | The node is the root node of a classification tree. (2) | |
TsTree | The root node of a time series tree that corresponds to a predictable time series. (16) | |
Unknown | An unknown node type. (6) |
Замечания
When you retrieve nodes from mining model content, the node type may be returned as an integer value that represents the enumeration. These integer values are provided in parentheses.