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.BaseModelImplement 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:
objectImplements 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.