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    Classification
    • 06 Jan 2023
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    Contents

    Classification

    • Updated on 06 Jan 2023
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    Article summary

    Description

    The Classification node is used to apply a classification model to a data set. Classification can be on text and non-text data.


    Configuration Options

    Basic Configuration Options

    SettingDescription\Parameters
    Split ColumnsThe selected column(s) will be used to split the data set over to build additional models.
    Model TypeThe model type.

    Options
    • LogisticRegression
    • RandomForest
    • GradientBoostedTrees
    Model ActionRebuildAndScore will automatically rebuild the model everytime you score.

    Options
    • Score
    • RebuildAndScore
    TargetThe column we are predicting; can be continous or categorical in nature.
    Role ColumnSplits input data into SCORING or TRAINING. Builds the model from TRAINING data.
    PredictorsThe columns we are using to predict.

    Advanced Configuration Options

    Random Forest model specific settings

    SettingDescription
    Output Local Variable ImportanceOutput local variable importance (for binary targets only, 0/1).
    Number of Top Local VariablesNumber of local variables to output.

    Actions

    ActionDescription
    PreviewAfter configuring the node, the combined result set can be previewed by clicking the Preview button.
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