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I discard the preprocess function using tutorial here, but I still get an error:
Traceback (most recent call last): File "/home/kevin/.conda/envs/dl/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap self.run() File "/home/kevin/.conda/envs/dl/lib/python3.8/multiprocessing/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/pynisher/limit_function_call.py", line 133, in subprocess_func return_value = ((func(*args, **kwargs), 0)) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/smbo.py", line 160, in _calculate_metafeatures_encoded result = calculate_all_metafeatures_encoded_labels( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/metalearning/metafeatures/metafeatures.py", line 1115, in calculate_all_metafeatures_encoded_labels return calculate_all_metafeatures( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/metalearning/metafeatures/metafeatures.py", line 1194, in calculate_all_metafeatures X_transformed = DPP.fit_transform(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/base.py", line 699, in fit_transform return self.fit(X, **fit_params).transform(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/pipeline/components/data_preprocessing/feature_type.py", line 216, in fit self.column_transformer.fit(X, y) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/compose/_column_transformer.py", line 470, in fit self.fit_transform(X, y=y) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/compose/_column_transformer.py", line 507, in fit_transform result = self._fit_transform(X, y, _fit_transform_one) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/compose/_column_transformer.py", line 434, in _fit_transform return Parallel(n_jobs=self.n_jobs)( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 1085, in __call__ if self.dispatch_one_batch(iterator): File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 901, in dispatch_one_batch self._dispatch(tasks) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 819, in _dispatch job = self._backend.apply_async(batch, callback=cb) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/_parallel_backends.py", line 208, in apply_async result = ImmediateResult(func) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/_parallel_backends.py", line 597, in __init__ self.results = batch() File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 288, in __call__ return [func(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 288, in <listcomp> return [func(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/utils/fixes.py", line 222, in __call__ return self.function(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 754, in _fit_transform_one res = transformer.fit_transform(X, y, **fit_params) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 378, in fit_transform Xt = self._fit(X, y, **fit_params_steps) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 303, in _fit X, fitted_transformer = fit_transform_one_cached( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/memory.py", line 349, in __call__ return self.func(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 754, in _fit_transform_one res = transformer.fit_transform(X, y, **fit_params) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/base.py", line 699, in fit_transform return self.fit(X, **fit_params).transform(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/pipeline/components/data_preprocessing/imputation/categorical_imputation.py", line 58, in fit self.preprocessor.fit(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/impute/_base.py", line 288, in fit X = self._validate_input(X, in_fit=True) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/impute/_base.py", line 266, in _validate_input raise ValueError("SimpleImputer does not support data with dtype " ValueError: SimpleImputer does not support data with dtype bool. Please provide either a numeric array (with a floating point or integer dtype) or categorical data represented either as an array with integer dtype or an array of string values with an object dtype.
Besides, I get lots of warnings like [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 318 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 304 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 500 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 150 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 452 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 120 not found
Or sometimes, I will get an warnings like [WARNING] [2023-11-21 01:36:01,750:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:03,774:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:05,645:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:06,056:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:06,413:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:06,826:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:08,945:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:10,966:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:12,964:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:14,894:Client-EnsembleBuilder] No runs were available to build an ensemble from
How to solve theses problems. I would really appreciate your help!!!
The text was updated successfully, but these errors were encountered:
I discard the preprocess function using tutorial here, but I still get an error:
Traceback (most recent call last): File "/home/kevin/.conda/envs/dl/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap self.run() File "/home/kevin/.conda/envs/dl/lib/python3.8/multiprocessing/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/pynisher/limit_function_call.py", line 133, in subprocess_func return_value = ((func(*args, **kwargs), 0)) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/smbo.py", line 160, in _calculate_metafeatures_encoded result = calculate_all_metafeatures_encoded_labels( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/metalearning/metafeatures/metafeatures.py", line 1115, in calculate_all_metafeatures_encoded_labels return calculate_all_metafeatures( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/metalearning/metafeatures/metafeatures.py", line 1194, in calculate_all_metafeatures X_transformed = DPP.fit_transform(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/base.py", line 699, in fit_transform return self.fit(X, **fit_params).transform(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/pipeline/components/data_preprocessing/feature_type.py", line 216, in fit self.column_transformer.fit(X, y) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/compose/_column_transformer.py", line 470, in fit self.fit_transform(X, y=y) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/compose/_column_transformer.py", line 507, in fit_transform result = self._fit_transform(X, y, _fit_transform_one) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/compose/_column_transformer.py", line 434, in _fit_transform return Parallel(n_jobs=self.n_jobs)( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 1085, in __call__ if self.dispatch_one_batch(iterator): File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 901, in dispatch_one_batch self._dispatch(tasks) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 819, in _dispatch job = self._backend.apply_async(batch, callback=cb) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/_parallel_backends.py", line 208, in apply_async result = ImmediateResult(func) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/_parallel_backends.py", line 597, in __init__ self.results = batch() File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 288, in __call__ return [func(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/parallel.py", line 288, in <listcomp> return [func(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/utils/fixes.py", line 222, in __call__ return self.function(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 754, in _fit_transform_one res = transformer.fit_transform(X, y, **fit_params) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 378, in fit_transform Xt = self._fit(X, y, **fit_params_steps) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 303, in _fit X, fitted_transformer = fit_transform_one_cached( File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/joblib/memory.py", line 349, in __call__ return self.func(*args, **kwargs) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/pipeline.py", line 754, in _fit_transform_one res = transformer.fit_transform(X, y, **fit_params) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/base.py", line 699, in fit_transform return self.fit(X, **fit_params).transform(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/autosklearn/pipeline/components/data_preprocessing/imputation/categorical_imputation.py", line 58, in fit self.preprocessor.fit(X) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/impute/_base.py", line 288, in fit X = self._validate_input(X, in_fit=True) File "/home/kevin/.conda/envs/dl/lib/python3.8/site-packages/sklearn/impute/_base.py", line 266, in _validate_input raise ValueError("SimpleImputer does not support data with dtype " ValueError: SimpleImputer does not support data with dtype bool. Please provide either a numeric array (with a floating point or integer dtype) or categorical data represented either as an array with integer dtype or an array of string values with an object dtype.
Besides, I get lots of warnings like
[WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 318 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 304 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 500 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 150 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 452 not found [WARNING] [2023-11-21 02:16:00,936:Client-AutoMLSMBO(1)::96c3c0d8-87d0-11ee-b866-b1f592002a1c] Configuration 120 not found
Or sometimes, I will get an warnings like
[WARNING] [2023-11-21 01:36:01,750:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:03,774:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:05,645:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:06,056:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:06,413:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:06,826:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:08,945:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:10,966:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:12,964:Client-EnsembleBuilder] No runs were available to build an ensemble from [WARNING] [2023-11-21 01:36:14,894:Client-EnsembleBuilder] No runs were available to build an ensemble from
How to solve theses problems. I would really appreciate your help!!!
The text was updated successfully, but these errors were encountered: