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Retrieve variable range of decision tree node



    varRange = nodeVariableRange(tree,nodeID) returns the range of predictor variables varRange at the tree node specified by nodeID.

    varRange = nodeVariableRange(tree,nodeID,OmitUnusedVariables=omitUnusedVars) also specifies whether to omit the unused predictor variables from the returned varRange.


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    Create a decision tree for classification, and retrieve the range of variables at a specified node of the decision tree.

    Load the census1994 data set. The table adultdata contains six numeric and eight categorical variables.

    load census1994

    Train a classification tree based on the features contained in adultdata and the class labels in adultdata.salary. Limit the number of splits in the tree by specifying the name-value argument MaxNumSplits.

    tree = fitctree(adultdata,"salary",MaxNumSplits=31)
    tree = 
               PredictorNames: {1x14 cell}
                 ResponseName: 'salary'
        CategoricalPredictors: [2 4 6 7 8 9 10 14]
                   ClassNames: [<=50K    >50K]
               ScoreTransform: 'none'
              NumObservations: 32561
      Properties, Methods

    tree is a trained ClassificationTree model for classification.

    View the graphical display of the trained classification tree.


    {"String":"Figure Classification tree viewer contains an axes object and other objects of type uimenu, uicontrol. The axes object contains 84 objects of type line, text.","Tex":[],"LaTex":[]}

    Retrieve the range of predictor variables at node 10.

    varRange = nodeVariableRange(tree,10)
    varRange = struct with fields:
                 age: [-Inf 20.5000]
        relationship: [Not-in-family    Other-relative    Own-child    Unmarried]
        capital_gain: [7.0735e+03 Inf]

    Input Arguments

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    Decision tree model, specified as one of the following:

    Node in the decision tree, specified as a positive integer scalar. nodeID must be less than or equal to the number of nodes in the decision tree.

    Data Types: single | double

    Indicator to omit unused predictor variables from varRange, specified as a numeric or logical 1 (true) or 0 (false).

    Output Arguments

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    Variable range at the decision tree node, returned as a structure. If a predictor variable is numeric, the corresponding field of varRange is a 1-by-2 numeric vector containing the lower and upper bounds. If a predictor variable is categorical, the corresponding field of varRange is a categorical array containing the categories subgroup.

    Extended Capabilities

    Version History

    Introduced in R2020a