frame

ibex.frame(est)[source]
Parameters:est – either an estimator class or an estimator object. The class (or class of the object) should subclass sklearn.base.BaseEstimator.
Returns:
If est is a class, returns a class; if est is an object,
returns an object. Note that the result will subclass est and ibex.FrameMixin

Example

>>> from sklearn import linear_model
>>> from ibex import frame

We can use frame to adapt an object:

>>> prd = frame(linear_model.LinearRegression())
>>> prd
Adapter[LinearRegression](copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)

We can use frame to adapt a class:

>>> PdLinearRegression = frame(linear_model.LinearRegression)
>>> PdLinearRegression()
Adapter[LinearRegression](copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)

>>> PdLinearRegression(fit_intercept=False)
Adapter[LinearRegression](copy_X=True, fit_intercept=False, n_jobs=1, normalize=False)