Base Module

Base module includes three main classes:

These classes implement attributes and methods which are common to all models and classifiers.

class scripts.base.BaseClassifier

Bases: scripts.base._base.BaseModel

Implement methods and attributes common for all classifiers.

classes()

Return unique classes from the given training dataset.

Returns

Python iterable with all the unique classses.

Return type

Iterable

Raises

ModelNotFittedError – If the model has not been fitter yet.

number_of_classes()

Return number of unique classes based on the provided training dataset.

Returns

Number of unique classses.

Return type

int

Raises

ModelNotFittedError – If the model has not been fitter yet.

score()

Return training accuracy score.

Returns

Training accuracy score.

Return type

float

Raises

ModelNotFittedError – If the model has not been fitter yet.

class scripts.base.BaseModel

Bases: object

Implements generic attributes and methods for each ML model.

Warning

Don’t use as a classifier or regressor. This class merely serves as a superclass from which other models inherit for the purpose of code reusability.

is_fitted()

Is given model fitted?

Returns

Return type

bool

number_of_features()

Returns number of features within given training data-set.

Returns

Number of features.

Return type

int

Raises

ModelNotFittedError – If the model has not been fitter yet.

number_of_training_samples()

Return number provided training samples.

Returns

number provided training samples

Return type

int

Raises

ModelNotFittedError – If the model has not been fitter yet.