MAMUT API ========= .. meta:: :description: API reference for the MAMUT automated tabular classification workflow. :keywords: MAMUT API, Mamut class, automated classification, Python API The main public API is ``Mamut``. Import it with ``from mamut import Mamut`` to fit candidate models, select the best pipeline, generate predictions, create reports, and save model artifacts. The public prediction surface is ``best_model_``, ``predict``, and ``predict_proba``. Internal fitted estimators are also exposed for inspection through attributes such as ``raw_fitted_models_`` and ``validation_summary_``, but these are primarily diagnostics for reports and model comparison. Mamut ----- .. autoclass:: mamut.wrapper.Mamut :show-inheritance: Common Methods ~~~~~~~~~~~~~~ .. automethod:: mamut.wrapper.Mamut.fit :no-index: .. automethod:: mamut.wrapper.Mamut.predict :no-index: .. automethod:: mamut.wrapper.Mamut.predict_proba :no-index: .. automethod:: mamut.wrapper.Mamut.evaluate :no-index: .. automethod:: mamut.wrapper.Mamut.generate_evidence :no-index: .. automethod:: mamut.wrapper.Mamut.save_best_model :no-index: .. automethod:: mamut.wrapper.Mamut.create_ensemble :no-index: .. automethod:: mamut.wrapper.Mamut.create_greedy_ensemble :no-index: Model Selection --------------- ``ModelSelector`` is used internally by :class:`mamut.wrapper.Mamut` to compare supported estimators and optimize hyperparameters. Most users should configure model search through ``Mamut`` instead of instantiating ``ModelSelector`` directly. .. autoclass:: mamut.model_selection.ModelSelector :members: :show-inheritance: Evaluation ---------- ``ModelEvaluator`` is used internally by ``Mamut.evaluate`` to produce the HTML report and plots. .. autoclass:: mamut.evaluation.ModelEvaluator :members: :show-inheritance: Evidence -------- Evidence helpers power the validation integrity, leakage, baseline, and score stability sections of ``Mamut.evaluate``. .. automodule:: mamut.evidence :members: