easypheno.model.xgboost

Module Contents

Classes

XgBoost

Implementation of a class for XGBoost.

class easypheno.model.xgboost.XgBoost(task, optuna_trial, encoding=None, n_outputs=1)

Bases: easypheno.model._sklearn_model.SklearnModel

Implementation of a class for XGBoost.

See BaseModel for more information on the attributes.

Parameters

• task (str) –

• optuna_trial (optuna.trial.Trial) –

• encoding (str) –

• n_outputs (int) –

standard_encoding = 012

possible_encodings = ['012']

define_model(self)

Definition of the actual prediction model.

See BaseModel for more information.

Return type

xgboost.XGBModel

define_hyperparams_to_tune(self)

See BaseModel for more information on the format.

Further params that potentially can be optimized

'reg_lambda': {
    'datatype': 'float',
    'lower_bound': 0,
    'upper_bound': 1000,
    'step': 10
}

Return type

dict