MiningNodeType Enumeration
Represents the type of the MiningContentNode.
Espace de noms: Microsoft.AnalysisServices.AdomdServer
Assembly: msmgdsrv (in msmgdsrv.dll)
Syntaxe
'Déclaration
<SuppressMessageAttribute("Microsoft.Design", "CA1008:EnumsShouldHaveZeroValue")> _
Public Enumeration MiningNodeType
[SuppressMessageAttribute("Microsoft.Design", "CA1008:EnumsShouldHaveZeroValue")]
public enum MiningNodeType
[SuppressMessageAttribute(L"Microsoft.Design", L"CA1008:EnumsShouldHaveZeroValue")]
public enum class MiningNodeType
/** @attribute SuppressMessageAttribute("Microsoft.Design", "CA1008:EnumsShouldHaveZeroValue") */
public enum MiningNodeType
SuppressMessageAttribute("Microsoft.Design", "CA1008:EnumsShouldHaveZeroValue")
public enum MiningNodeType
Members
| Member name | Description |
|---|---|
| AssociationRule | The node represents an association rule detected by the algorithm. |
| Cluster | The node represents a cluster detected by the algorithm. |
| 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. |
| Distribution | The node represents a leaf of a classification tree. |
| InputAttribute | The node corresponds to a predictable attribute. |
| InputAttributeState | The node contains statistics about the states of an input attribute. |
| Interior | The node represents an interior split node in a classification tree. |
| ItemSet | The node represents an itemset detected by the algorithm |
| Model | The root content node. This node applies to all algorithms. |
| NaiveBayesMarginalStatNode | The node containing marginal statistics about the training set, stored in a format used by the Naïve Bayes algorithm. |
| NNetHiddenLayer | The node which groups together the nodes that describe the hidden layer. This type is used with neural network algorithms. |
| NNetHiddenNode | The node is a node of the hidden layer. This type is used with neural network algorithms. |
| NNetInputLayer | The node which groups together the nodes of the input layer. This type is used with neural network algorithms. |
| 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. |
| 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. |
| NNetOutputLayer | The node which groups together the nodes of the output layer. This type is used with neural network algorithms. |
| 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. |
| NNetSubnetwork | The node contains one sub-network. This type is used with neural network algorithms. |
| PredictableAttribute | The node corresponds to a predictable attribute. |
| RegressionTreeRoot | The node is the root of a regression tree. |
| 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. |
| TimeSeries | The non-root node of a time series tree. |
| 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. |
| Tree | The node is the root node of a classification tree. |
| TsTree | The root node of a time series tree that corresponds to a predictable time series. |
| Unknown | An unknown node type. |
Plateformes
Plateformes de développement
Pour obtenir la liste des plateformes prises en charge, consultez Configuration matérielle et logicielle requise pour l'installation de SQL Server 2005.
Plateformes cibles
Pour obtenir la liste des plateformes prises en charge, consultez Configuration matérielle et logicielle requise pour l'installation de SQL Server 2005.