bpllib.TemplateEstimator

class bpllib.TemplateEstimator(demo_param='demo_param')

A template estimator to be used as a reference implementation.

For more information regarding how to build your own estimator, read more in the User Guide.

Parameters:

demo_paramstr, default=’demo_param’

A parameter used for demonstation of how to pass and store paramters.

Examples

>>> from bpllib import TemplateEstimator
>>> import numpy as np
>>> X = np.arange(100).reshape(100, 1)
>>> y = np.zeros((100, ))
>>> estimator = TemplateEstimator()
>>> estimator.fit(X, y)
TemplateEstimator()

__init__(demo_param='demo_param')

fit(X, y)

A reference implementation of a fitting function.

Parameters:

X{array-like, sparse matrix}, shape (n_samples, n_features)

The training input samples.

yarray-like, shape (n_samples,) or (n_samples, n_outputs)

The target values (class labels in classification, real numbers in regression).

Returns:

selfobject

Returns self.

predict(X)

A reference implementation of a predicting function.

Parameters:

X{array-like, sparse matrix}, shape (n_samples, n_features)

The training input samples.

Returns:

yndarray, shape (n_samples,)

Returns an array of ones.