easypheno.model._param_free_base_model

Module Contents

Classes

ParamFreeBaseModel

BaseModel parent class for all models that do not have hyperparameters, e.g. BLUP.

class easypheno.model._param_free_base_model.ParamFreeBaseModel(task, encoding=None)

Bases: abc.ABC

BaseModel parent class for all models that do not have hyperparameters, e.g. BLUP.

Every model must be based on ParamFreeBaseModel directly or ParamFreeBaseModel’s child classes.

Please add super().__init__(PARAMS) to the constructor in case you override it in a child class

Attributes

Class attributes

• standard_encoding (str): the standard encoding for this model

• possible_encodings (List<str>): a list of all encodings that are possible according to the model definition

Instance attributes

• task (str): ML task (‘regression’ or ‘classification’) depending on target variable

• encoding (str): the encoding to use (standard encoding or user-defined)

Parameters

• task (str) – ML task (regression or classification) depending on target variable

• encoding (str) – the encoding to use (standard encoding or user-defined)

property standard_encoding(cls)

the standard encoding for this model

property possible_encodings(cls)

a list of all encodings that are possible according to the model definition

abstract fit(self, X, y)

Method that fits the model based on features X and targets y

Parameters

• X (numpy.array) – feature matrix for retraining

• y (numpy.array) – target vector

Returns

numpy array with values predicted for X

Return type

numpy.array

abstract predict(self, X_in)

Method that predicts target values based on the input X_in

Parameters

X_in (numpy.array) – feature matrix as input

Returns

numpy array with the predicted values

Return type

numpy.array

save_model(self, path, filename)

Persist the whole model object on a hard drive (can be loaded with load_model)

Parameters

• path (pathlib.Path) – path where the model will be saved

• filename (str) – filename of the model