I got the data from datasets and imported its working fine.
But when I try to compile this code below:
from pycaret.classification import ClassificationExperiment
s = ClassificationExperiment()
s.setup(data, target = 'Class variable', session_id = 123)
Atfer I got this error "AttributeError: module 'pycaret' has no attribute 'utils'":
Number of times pregnant Plasma glucose concentration a 2 hours in an oral glucose tolerance test Diastolic blood pressure (mm Hg) Triceps skin fold thickness (mm) 2-Hour serum insulin (mu U/ml) Body mass index (weight in kg/(height in m)^2) Diabetes pedigree function Age (years) Class variable
0 6 148 72 35 0 33.6 0.627 50 1
1 1 85 66 29 0 26.6 0.351 31 0
2 8 183 64 0 0 23.3 0.672 32 1
3 1 89 66 23 94 28.1 0.167 21 0
4 0 137 40 35 168 43.1 2.288 33 1
Output exceeds the size limit. Open the full output data in a text editor
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AttributeError Traceback (most recent call last)
Cell In[33], line 3
1 from pycaret.classification import ClassificationExperiment
2 s = ClassificationExperiment()
----> 3 s.setup(data, target = 'Class variable', session_id = 123)
File ~/.local/lib/python3.10/site-packages/pycaret/classification/oop.py:781, in ClassificationExperiment.setup(self, data, data_func, target, index, train_size, test_data, ordinal_features, numeric_features, categorical_features, date_features, text_features, ignore_features, keep_features, preprocess, create_date_columns, imputation_type, numeric_imputation, categorical_imputation, iterative_imputation_iters, numeric_iterative_imputer, categorical_iterative_imputer, text_features_method, max_encoding_ohe, encoding_method, rare_to_value, rare_value, polynomial_features, polynomial_degree, low_variance_threshold, group_features, group_names, drop_groups, remove_multicollinearity, multicollinearity_threshold, bin_numeric_features, remove_outliers, outliers_method, outliers_threshold, fix_imbalance, fix_imbalance_method, transformation, transformation_method, normalize, normalize_method, pca, pca_method, pca_components, feature_selection, feature_selection_method, feature_selection_estimator, n_features_to_select, custom_pipeline, custom_pipeline_position, data_split_shuffle, data_split_stratify, fold_strategy, fold, fold_shuffle, fold_groups, n_jobs, use_gpu, html, session_id, system_log, log_experiment, experiment_name, experiment_custom_tags, log_plots, log_profile, log_data, engine, verbose, memory, profile, profile_kwargs)
764 self._prepare_folds(
765 fold_strategy=fold_strategy,
766 fold=fold,
767 fold_shuffle=fold_shuffle,
768 fold_groups=fold_groups,
769 )
771 self._prepare_column_types(
772 ordinal_features=ordinal_features,
773 numeric_features=numeric_features,
(...)
778 keep_features=keep_features,
779 )
--> 781 self._set_exp_model_engines(
782 container_default_engines=get_container_default_engines(),
783 engine=engine,
784 )
786 # Preprocessing ============================================ >>
...
File ~/.local/lib/python3.10/site-packages/pycaret/containers/base_container.py:64, in BaseContainer.get_class_name(self)
63 def get_class_name(self):
---> 64 return pycaret.utils.generic.get_class_name(self.class_def)
AttributeError: module 'pycaret' has no attribute 'utils'
I excepted this output:
