Classification

  • Published on Jan 6, 2023
  • 1 minute(s) read
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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

Setting Description\Parameters
Split Columns The selected column(s) will be used to split the data set over to build additional models.
Model Type The model type.

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

Options
  • Score
  • RebuildAndScore
Target The column we are predicting; can be continous or categorical in nature.
Role Column Splits input data into SCORING or TRAINING. Builds the model from TRAINING data.
Predictors The columns we are using to predict.

Advanced Configuration Options

Random Forest model specific settings

Setting Description
Output Local Variable Importance Output local variable importance (for binary targets only, 0/1).
Number of Top Local Variables Number of local variables to output.

Actions

Action Description
Preview After configuring the node, the combined result set can be previewed by clicking the Preview button.