Classification

  • Updated on Jan 13, 2023
  • Published on Mar 29, 2022
  • 1 minute(s) read
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Description

The Classification node applies 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 columns 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 every time you score.

Options
  • Score
  • RebuildAndScore
Target The column we are predicting; can be continuous or categorical in nature.
Role Column Splits input data into SCORING or TRAINING. Builds the model from TRAINING data.
Predictors The columns with which 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 Once the node is configured, the combined result set can be previewed at any time.