MMM.fit#

MMM.fit(X, y=None, progressbar=True, predictor_names=None, random_seed=None, **kwargs)#

Fit a model using the data passed as a parameter. Sets attrs to inference data of the model.

Parameters:

Xarray_like if sklearn is available, otherwise array, shape (n_obs, n_features): The training input samples.
yarray_like if sklearn is available, otherwise array, shape (n_obs,): The target values (real numbers).
progressbarbool: Specifies whether the fit progressbar should be displayed
predictor_names: Optional[List[str]] = None,: Allows for custom naming of predictors given in a form of 2dArray Allows for naming of predictors when given in a form of np.ndarray, if not provided the predictors will be named like predictor1, predictor2…
random_seedOptional[RandomState]: Provides sampler with initial random seed for obtaining reproducible samples
**kwargsAny: Custom sampler settings can be provided in form of keyword arguments.

Returns:

>>> :obj:`model` = :obj:`MyModel`\()
    ..

>>> :obj:`idata` = :obj:`model.fit`\(X,y)
    ..