MiningNodeType MiningNodeType MiningNodeType Enum

Definition

Represents the type of the MiningContentNode.

public enum class MiningNodeType
public enum MiningNodeType
Public Enum MiningNodeType
Inheritance
MiningNodeTypeMiningNodeTypeMiningNodeType

Fields

ArimaAutoRegressive ArimaAutoRegressive ArimaAutoRegressive 29

The node that contains the autoregressive coefficient for a single term in an ARIMA model. (29)

ArimaMovingAverage ArimaMovingAverage ArimaMovingAverage 30

The node that contains the moving average coefficient for a single term in an ARIMA model. (30)

ArimaPeriodicStructure ArimaPeriodicStructure ArimaPeriodicStructure 28

The node that represents a periodic structure in an ARIMA model. (28)

ArimaRoot ArimaRoot ArimaRoot 27

The root node of an ARIMA model. (27)

AssociationRule AssociationRule AssociationRule 8

The node represents an association rule detected by the algorithm. (8)

Cluster Cluster Cluster 5

The node represents a cluster detected by the algorithm. (5)

CustomBase CustomBase CustomBase 1000

Represents the starting point for custom node types. Custom node types must be integers greater in value than this constant. (1000) This type is used by plug-in algorithms.

Distribution Distribution Distribution 4

The node represents a leaf of a classification tree. (4)

InputAttribute InputAttribute InputAttribute 10

The node corresponds to a predictable attribute. (10)

InputAttributeState InputAttributeState InputAttributeState 11

The node contains statistics about the states of an input attribute. (11)

Interior Interior Interior 3

The node represents an interior split node in a classification tree. (3)

ItemSet ItemSet ItemSet 7

The node represents an itemset detected by the algorithm. (7)

Model Model Model 1

The root content node. This node applies to all algorithms. (1)

NaiveBayesMarginalStatNode NaiveBayesMarginalStatNode NaiveBayesMarginalStatNode 26

The node containing marginal statistics about the training set, stored in a format used by the Naïve Bayes algorithm. (26)

NNetHiddenLayer NNetHiddenLayer NNetHiddenLayer 19

The node that groups together the nodes that describe the hidden layer. This type is used with neural network algorithms. (19)

NNetHiddenNode NNetHiddenNode NNetHiddenNode 22

The node is a node of the hidden layer. This type is used with neural network algorithms. (22)

NNetInputLayer NNetInputLayer NNetInputLayer 18

The node that groups together the nodes of the input layer. This type is used with neural network algorithms. (18)

NNetInputNode NNetInputNode NNetInputNode 21

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 NNetMarginalNode NNetMarginalNode 24

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 NNetOutputLayer NNetOutputLayer 20

The node that groups together the nodes of the output layer. This type is used with neural network algorithms. (21)

NNetOutputNode NNetOutputNode NNetOutputNode 23

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 NNetSubnetwork NNetSubnetwork 17

The node contains one sub-network. This type is used with neural network algorithms. (17)

PredictableAttribute PredictableAttribute PredictableAttribute 9

The node corresponds to a predictable attribute. (9)

RegressionTreeRoot RegressionTreeRoot RegressionTreeRoot 25

The node is the root of a regression tree. (25)

Sequence Sequence Sequence 13

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 TimeSeries TimeSeries 15

The non-root node of a time series tree. (15)

Transition Transition Transition 14

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 Tree Tree 2

The node is the root node of a classification tree. (2)

TsTree TsTree TsTree 16

The root node of a time series tree that corresponds to a predictable time series. (16)

Unknown Unknown Unknown 6

An unknown node type. (6)

Remarks

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.

Applies to