Dask client with only 1 worker Note ---- May create deadlocks with logging and pynisher

Decorator for adding helper functions to a "dictionary". This behaves like a function decorating a function, not a class decorating a

Decorator for adding metafeature functions to a "dictionary" of metafeatures. This behaves like a function decorating a function, not

The durations (cpu, wall)

Mark a parameter for pytest parametrize that it should fail ..code:: python @parametrize("number", [2, 3, fails(5, "some reason")])

Fit an ensemble given predictions of base models and targets. Ensemble building maximizes performance (in contrast to hyperparameter

Fit the ensemble Parameters ---------- base_models_predictions: np.ndarray shape = (n_base_models, n_data_points,

The fit function calls the fit function of the underlying scikit-learn model and returns `self`. Parameters ----------

A short function to fit and create an ensemble. It is just a wrapper to easily send a request to dask to create an ensemble and clean

Fit an ensemble to models trained during an optimization process. All parameters are ``None`` by default. If no other value is given,

Fits and individual pipeline configuration and returns the result to the user. The Estimator constraints are honored, for example the

Returns the params if fitted successfully, else None if an acceptable error occurs

Allows retrieving additional run information from the pipeline. Can be overridden by subclasses to return additional information to t