Assembly: Stat;
Namespace: Prognoz.Platform.Interop.Stat;
The ISmRandomForest interface is used to work with the Random Forest decision tree ensemble.
ISmRandomForest
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.
| 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. |
| Property name | Brief description | |
| The DisplayName property returns the displayed method name. | ||
| The ErrorByStatus property returns an error message by the error number. | ||
| The Errors property returns a message with all the errors and warnings. | ||
| The Name property returns the internal method name. | ||
| The PerformanceTime property returns method execution time. | ||
| The Status property returns the method execution status. | ||
| The SupportsR property returns whether statistical method can be calculated via R package. | ||
| The UseR property determines whether statistical method is calculated via the R package. | ||
| The WarningByStatus property returns a warning text by its number. | ||
| The Warnings property returns the warnings that occurred at method calculation. | ||
| The WarningsCount property returns the number of warnings that occurred at the method calculation. | ||
| The WarningsNumbers property returns numbers of warnings that occurred at the method calculation. |
| Method Name | Brief description | |
| The Clone method clones a statistical method object. | ||
| The Execute method executes a statistical method. | ||
| The LoadFromXML method loads statistical method settings from XML code. | ||
| The SaveToXML method unloads statistical method settings to XML code. |
See also: