.. _auto_dataset_classifier: *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 ------ .. list-table:: :header-rows: 1 :widths: 20 20 20 20 20 20 * - 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 ------- .. list-table:: :header-rows: 1 :widths: 20 20 20 20 * - 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 `_ .. raw:: html

Auto-generated from transformation schema. Worker id: dataset_classifier. Schema hash: 516eaa1abf07. Hand-curated docs in workerexamples/ override this page when present.