from enum import Enum
[docs]class ModelFamily(Enum):
"""Enum for family of machine learning models."""
K_NEIGHBORS = 'k_neighbors'
"""K Nearest Neighbors model family."""
RANDOM_FOREST = 'random_forest'
"""Random Forest model family."""
SVM = 'svm'
"""SVM model family."""
XGBOOST = 'xgboost'
"""XGBoost model family."""
LIGHTGBM = 'lightgbm'
"""LightGBM model family."""
LINEAR_MODEL = 'linear_model'
"""Linear model family."""
CATBOOST = 'catboost'
"""CatBoost model family."""
EXTRA_TREES = 'extra_trees'
"""Extra Trees model family."""
ENSEMBLE = 'ensemble'
"""Ensemble model family."""
DECISION_TREE = 'decision_tree'
"""Decision Tree model family."""
ARIMA = 'ARIMA'
"""ARIMA model family."""
BASELINE = 'baseline'
"""Baseline model family."""
NONE = 'none'
"""None"""
def __str__(self):
model_family_dict = {ModelFamily.K_NEIGHBORS.name: "K Nearest Neighbors",
ModelFamily.RANDOM_FOREST.name: "Random Forest",
ModelFamily.SVM.name: "SVM",
ModelFamily.XGBOOST.name: "XGBoost",
ModelFamily.LIGHTGBM.name: "LightGBM",
ModelFamily.LINEAR_MODEL.name: "Linear",
ModelFamily.CATBOOST.name: "CatBoost",
ModelFamily.EXTRA_TREES.name: "Extra Trees",
ModelFamily.DECISION_TREE.name: "Decision Tree",
ModelFamily.BASELINE.name: "Baseline",
ModelFamily.ENSEMBLE.name: "Ensemble",
ModelFamily.ARIMA.name: "ARIMA",
ModelFamily.NONE.name: "None"}
return model_family_dict[self.name]
def __repr__(self):
return "ModelFamily." + self.name
def is_tree_estimator(self):
"""Checks whether the estimator's model family uses trees."""
tree_estimators = {self.CATBOOST, self.EXTRA_TREES, self.RANDOM_FOREST,
self.DECISION_TREE, self.XGBOOST, self.LIGHTGBM}
return self in tree_estimators