Assembly: Ms;
Namespace: Prognoz.Platform.Interop.Ms;
The IDmRandomForest interface is used to set up calculation parameters of the Random Forest algorithm of the Decision Tree Ensembles method on data mining.
IDmRandomForest
Random forest is machine-learning algorithm to solve regression and classification tasks based on decision tree ensemble.
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 | |
The TreeSizeSpecification property returns tree specification. |
Method name | Brief description | |
The FillTarget method unloads missing data treatment results into the data source |
Property name | Brief description | |
The Target property determines the field index of the data source, containing analyzed information. |
Property name | Brief description | |
The Attributes property determines the field indexes of the data source, containing factors for the analysis. |
Property name |
Brief description | |
The CrossValidation property returns cross-validation settings | ||
The DisplayName property returns the method name. | ||
The StatMethod property returns statistical method parameters used in analysis. |
Property name |
Brief description | |
The ForestSize property determines the number of trees in random forest. | ||
The LearningSamplePortion property determines sample proportion for learning of the tree. | ||
The NumberOfPredictors property determines the number of attributes, which form a random tree. |
See also: