DATASET CLASSIFIER¶
Applies a rule-based classifier to a dataset, assigning each row to a category based on user-defined filter/classification rules. Use this worker to label or segment dataset records without training an ML model.
When to use¶
Classification: process.
Tagged: classifier, dataset_classification, labeling, rule_based, segmentation.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Dataset | dataset_1 | dataset | — | Input dataset (tabular) whose rows are to be classified; connect any dataset output from an upstream worker — leave unconnected only if classification is to be run on a pre-loaded dataset. | |
| Classifications | classifications | classifier | — | Rule-based classifier definition (filter conditions and corresponding class labels) that drives the classification logic; the available filter fields are automatically derived from dataset_1. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| dataset_drop_columns_output_1 | dataset_drop_columns_output_1 | dataset | Output dataset identical in structure to the input but augmented with a classification label column indicating the assigned category for each row. |
Disciplines¶
- ai_ml.supervised.classification
- data.dataset.transform
Runnable example¶
A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=dataset_classifier
Auto-generated from transformation schema. Worker id: dataset_classifier. Schema hash: 516eaa1abf07. Hand-curated docs in workerexamples/ override this page when present.