streamline.models.gradient_boosting module

class streamline.models.gradient_boosting.CGBClassifier(cv_folds=3, scoring_metric='balanced_accuracy', metric_direction='maximize', random_state=None, cv=None, n_jobs=None)

Bases: BaseModel, ABC

Base Model Class for all ML Models

Parameters:

• model –

• model_name –

• cv_folds –

• scoring_metric –

• metric_direction –

• random_state –

• cv –

• sampler –

• n_jobs –

color = 'magenta'

model_name = 'Category Gradient Boosting'

objective(trial, params=None)

Unimplemented objective function stub, needs to be overridden :param trial: optuna trial object :param params: dict of optional params or None

small_name = 'CGB'

class streamline.models.gradient_boosting.GBClassifier(cv_folds=3, scoring_metric='balanced_accuracy', metric_direction='maximize', random_state=None, cv=None, n_jobs=None)

Bases: BaseModel, ABC

Base Model Class for all ML Models

Parameters:

• model –

• model_name –

• cv_folds –

• scoring_metric –

• metric_direction –

• random_state –

• cv –

• sampler –

• n_jobs –

color = 'cornflowerblue'

model_name = 'Gradient Boosting'

objective(trial, params=None)

Unimplemented objective function stub, needs to be overridden :param trial: optuna trial object :param params: dict of optional params or None

small_name = 'GB'

class streamline.models.gradient_boosting.LGBClassifier(cv_folds=3, scoring_metric='balanced_accuracy', metric_direction='maximize', random_state=None, cv=None, n_jobs=None)

Bases: BaseModel, ABC

Base Model Class for all ML Models

Parameters:

• model –

• model_name –

• cv_folds –

• scoring_metric –

• metric_direction –

• random_state –

• cv –

• sampler –

• n_jobs –

color = 'pink'

model_name = 'Light Gradient Boosting'

objective(trial, params=None)

Unimplemented objective function stub, needs to be overridden :param trial: optuna trial object :param params: dict of optional params or None

small_name = 'LGB'

class streamline.models.gradient_boosting.XGBClassifier(cv_folds=3, scoring_metric='balanced_accuracy', metric_direction='maximize', random_state=None, cv=None, n_jobs=None)

Bases: BaseModel, ABC

Base Model Class for all ML Models

Parameters:

• model –

• model_name –

• cv_folds –

• scoring_metric –

• metric_direction –

• random_state –

• cv –

• sampler –

• n_jobs –

color = 'cyan'

model_name = 'Extreme Gradient Boosting'

objective(trial, params=None)

Unimplemented objective function stub, needs to be overridden :param trial: optuna trial object :param params: dict of optional params or None

small_name = 'XGB'