SklearnModel

class mastml.models.SklearnModel(model, **kwargs)

Bases: BaseEstimator, TransformerMixin

Class to wrap any sklearn estimator, and provide some new dataframe functionality

Args:

model: (str), string denoting the name of an sklearn estimator object, e.g. KernelRidge

kwargs: keyword pairs of values to include for model, e.g. for KernelRidge can specify kernel, alpha, gamma values

Methods:

fit: method that fits the model parameters to the provided training data

Args:

X: (pd.DataFrame), dataframe of X features

y: (pd.Series), series of y target data

Returns:

fitted model

predict: method that evaluates model on new data to give predictions

Args:

X: (pd.DataFrame), dataframe of X features

as_frame: (bool), whether to return data as pandas dataframe (else numpy array)

Returns:

series or array of predicted values

help: method to output key information on class use, e.g. methods and parameters

Args:

None

Returns:

None, but outputs help to screen

Methods Summary

fit(X, y)
get_params([deep])	Get parameters for this estimator.
help()
predict(X[, as_frame])

Methods Documentation

fit(X, y)

get_params(deep=True)

Get parameters for this estimator.

Parameters

deepbool, default=True

If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns

paramsdict

Parameter names mapped to their values.

help()

predict(X, as_frame=True)