MiningNodeType Enumeration

아티클
12/15/2008

Represents the type of the MiningContentNode.

네임스페이스: Microsoft.AnalysisServices.AdomdServer
어셈블리: msmgdsrv (in msmgdsrv.dll)

구문

‘선언
<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.