IK
(пока запуск локально, спарк тяну через sdk)
(Spark 2.3.1) падает при инициализации new Pool()
(Spark 2.4.5) тест на классификацию из readme - Ok
Size: a a a
IK
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IK
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TB
Error: catboost/libs/fstr/calc_fstr.cpp:673: CalcFstr is not implemented for models with embeddings featuresпро попытке получить feature_importance
TB
File "/root/.pyenv/versions/3.8.6/lib/python3.8/site-packages/catboost/core.py", line 4302, in fit
self._fit(X, y, cat_features, text_features, embedding_features, None, sample_weight, None, None, None, None, baseline, use_best_model,
File "/root/.pyenv/versions/3.8.6/lib/python3.8/site-packages/catboost/core.py", line 1806, in _fit
self._train(
File "/root/.pyenv/versions/3.8.6/lib/python3.8/site-packages/catboost/core.py", line 1258, in _train
self._object._train(train_pool, test_pool, params, allow_clear_pool, init_model._object if init_model else None)
File "_catboost.pyx", line 4156, in _catboost._CatBoost._train
File "_catboost.pyx", line 4205, in _catboost._CatBoost._train
_catboost.CatBoostError: catboost/private/libs/feature_estimator/feature_estimator.h:35: Attempt to call single feature writer on packed feature writer
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Error: catboost/libs/fstr/calc_fstr.cpp:673: CalcFstr is not implemented for models with embeddings featuresпро попытке получить feature_importance
TB
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model = CatBoostClassifier(iterations=1000, task_type="GPU", devices='0')
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model = CatBoostClassifier(iterations=1000, task_type="GPU", devices='0')
AK
dF
TG

TG

TG

TG

SK
SK