# AutoMLClassifier **`class AutoMLClassifier(config)`** Bases: [`Classifier`](squirro.lib.nlp.steps.classifiers.Classifier.md#squirro.lib.nlp.steps.classifiers.Classifier) The AutoML [`Classifier`](squirro.lib.nlp.steps.classifiers.Classifier.md#squirro.lib.nlp.steps.classifiers.Classifier) uses the [autogluon tabular](https://auto.gluon.ai) library for AutoML **Input** - all input fields need to be of type [`str`](https://docs.python.org/3.11/library/stdtypes.html#str). **Output** - prediction of the extract as a string Parameters - `type` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)) – automl - `preset` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)) – Choose between presets “best_quality” “high_quality” “good_quality” “medium_quality” - `hyperparameters` ([`dict`](https://docs.python.org/3.11/library/stdtypes.html#dict)`, ``None`) – Hyperparameters for additional models. If None, the default hyperparameters are used. - `fit_parameters` ([`dict`](https://docs.python.org/3.11/library/stdtypes.html#dict)`, ``None`) – Parameters for the TabularPredictor.fit() function. If None, the default parameters are used. **Example** ```json { "step": "classifier", "type": "automl", "input_fields": ["extract"], "output_field": "prediction", "label_field": "label", "hyperparameters": {"FASTTEXT": []}, "fit_parameters": {"time_limit": 30, "num_bag_folds": 5} } ``` Methods SummaryMethods Documentation **`clean()`** Clean step **`evaluate(tabular_docs)`** **`load()`** Load a step **`process_batch(batch)`** Process a batch of documents. If not defined will default to using self.process_doc for each document in the batch. Parameters `batch` ([`list`](https://docs.python.org/3.11/library/stdtypes.html#list)`(`[`Document`](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)`)`) – List of documents Returns List of processed documents Return type [list](https://docs.python.org/3.11/library/stdtypes.html#list)([Document](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)) **`train(docs)`** Train on a step of a set of documents Parameters `docs` (`generator``(`[`Document`](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)`)`) – Generator of documents Returns Generator of processed documents Return type generator([Document](../technical/libnlp/base.md#squirro.lib.nlp.document.Document))