SmRandomForest

Assembly: Stat;

Namespace: Prognoz.Platform.Interop.Stat;

Description

The ISmRandomForest interface is used to work with the Random Forest decision tree ensemble.

Comments

Random forest. is a method of classification problem solution suggested by Leo Breiman. The method is a class of machine-learning algorithms.

Ensemble (committee) of decision trees is used to build decision rules. Objects are classified by means of voting: each tree of the created tree assigns the considered object to one of the categories. The category that scores the most of votes wins.

Fore.NET Syntax

Class to get analog of the SmRandomForest class:

None;

Class to get analog of the SmRandomForest class object:

SmRandomForestClass;

Class properties inherited from ISmRandomForest

	Property name	Brief description
	CategoriesList	The CategoriesList property returns a list of categories.
	ClassificationSummary	The ClassificationSummary property returns summary results of classification.
	Dependent	The Dependent property returns an explained series.
	ExplanatoriesCategorical	The ExplanatoriesCategorical property returns explanatory categorical series.
	ExplanatoriesContinuous	The ExplanatoriesContinuous property returns explanatory quantitative series.
	ExplanatoriesOrdered	The ExplanatoriesOrdered property returns explanatory ordinal series.
	FilledDependent	The FilledDependent property returns predicted classification.
	Forest	The Forest property returns an array of trees.
	ForestSize	The ForestSize property determines the number of trees in random forest.
	LearningSamplePortion	The LearningSamplePortion property determines sample proportion for learning of the tree.
	NumberOfPredictors	The NumberOfPredictors property determines the number of attributes, which form a random tree.
	ROCcurve	The ROCcurve property returns ROC curve parameters.
	Probability	The Probability property returns a two-dimensional array of probabilities, which determine whether observations are assigned to the selected categories.
	TreeSizeSpecification	The TreeSizeSpecification property returns tree specification.

Properties inherited from IStatMethod

	Property name	Brief description
	DisplayName	The DisplayName property returns the displayed method name.
	ErrorByStatus	The ErrorByStatus property returns an error message by the error number.
	Errors	The Errors property returns a message with all the errors and warnings.
	Name	The Name property returns the internal method name.
	PerformanceTime	The PerformanceTime property returns method execution time.
	Status	The Status property returns the method execution status.
	SupportsR	The SupportsR property returns whether statistical method can be calculated via R package.
	UseR	The UseR property determines whether statistical method is calculated via the R package.
	WarningByStatus	The WarningByStatus property returns a warning text by its number.
	Warnings	The Warnings property returns the warnings that occurred at method calculation.
	WarningsCount	The WarningsCount property returns the number of warnings that occurred at the method calculation.
	WarningsNumbers	The WarningsNumbers property returns numbers of warnings that occurred at the method calculation.

Methods inherited from IStatMethod

	Method Name	Brief description
	Clone	The Clone method clones a statistical method object.
	Execute	The Execute method executes a statistical method.
	LoadFromXML	The LoadFromXML method loads statistical method settings from XML code.
	SaveToXML	The SaveToXML method unloads statistical method settings to XML code.

See also:

Stat Assembly Classes