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Speed up catboost fit: change catboost default and automl parameter ranges #998

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merged 5 commits into from Jul 31, 2020
Merged

Speed up catboost fit: change catboost default and automl parameter ranges #998

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5421c39
Tune catboost hyperparameter ranges to reduce fit time
dsherry Jul 28, 2020
f2bec47
Use uniform distribution for catboost classifier params
dsherry Jul 30, 2020
ea864e3
Remove redundant parameter
dsherry Jul 31, 2020
de75aca
Make the same changes to catboost regressor
dsherry Jul 31, 2020
20a7962
Changelog
dsherry Jul 31, 2020
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1 change: 1 addition & 0 deletions docs/source/release_notes.rst
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Expand Up @@ -9,6 +9,7 @@ Release Notes
* Added `_compute_shap_values` and `normalize_values` to `pipelines/explanations` module :pr:`958`
* Added `_explain_prediction` feature which explains single predictions with SHAP :pr:`974`
* Added support for configuring logfile path using env var, and don't create logger if there are filesystem errors :pr:`975`
* Updated catboost estimators' default parameters and automl hyperparameter ranges to speed up fit time :pr:`998`
* Fixes
* Fixed ReadtheDocs warning failure regarding embedded gif :pr:`943`
* Removed incorrect parameter passed to pipeline classes in `_add_baseline_pipelines` :pr:`941`
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4 changes: 2 additions & 2 deletions evalml/pipelines/components/estimators/classifiers/catboost_classifier.py
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Expand Up @@ -20,7 +20,7 @@ class CatBoostClassifier(Estimator):
"""
name = "CatBoost Classifier"
hyperparameter_ranges = {
"n_estimators": Integer(10, 1000),
"n_estimators": Integer(4, 100),
"eta": Real(0.000001, 1),
"max_depth": Integer(4, 10),
}
Expand All @@ -30,7 +30,7 @@ class CatBoostClassifier(Estimator):
SEED_MIN = 0
SEED_MAX = SEED_BOUNDS.max_bound

def __init__(self, n_estimators=1000, eta=0.03, max_depth=6, bootstrap_type=None, random_state=0, **kwargs):
def __init__(self, n_estimators=10, eta=0.03, max_depth=6, bootstrap_type=None, random_state=0, **kwargs):
random_seed = get_random_seed(random_state, self.SEED_MIN, self.SEED_MAX)
parameters = {"n_estimators": n_estimators,
"eta": eta,
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6 changes: 3 additions & 3 deletions evalml/pipelines/components/estimators/regressors/catboost_regressor.py
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Expand Up @@ -18,17 +18,17 @@ class CatBoostRegressor(Estimator):
"""
name = "CatBoost Regressor"
hyperparameter_ranges = {
"n_estimators": Integer(10, 1000),
"n_estimators": Integer(4, 100),
"eta": Real(0.000001, 1),
"max_depth": Integer(1, 16),
"max_depth": Integer(4, 10),
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Interesting to note we already had the regressor set with this range, but not the classifier.

}
model_family = ModelFamily.CATBOOST
supported_problem_types = [ProblemTypes.REGRESSION]

SEED_MIN = 0
SEED_MAX = SEED_BOUNDS.max_bound

def __init__(self, n_estimators=1000, eta=0.03, max_depth=6, bootstrap_type=None, random_state=0, **kwargs):
def __init__(self, n_estimators=10, eta=0.03, max_depth=6, bootstrap_type=None, random_state=0, **kwargs):
random_seed = get_random_seed(random_state, self.SEED_MIN, self.SEED_MAX)
parameters = {"n_estimators": n_estimators,
"eta": eta,
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