mljar-supervised
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Problem about param ml_task="regression",
If I use this param, it will raise an issue below for all of the model, if it is deleted, the model works fine.
'<' not supported between instances of 'numpy.ndarray' and 'str' Traceback (most recent call last): File "C:\Users\ZHENGJ\AppData\Local\Programs\Python\Python39\lib\site-packages\supervised\base_automl.py", line 1195, in _fit trained = self.train_model(params) File "C:\Users\ZHENGJ\AppData\Local\Programs\Python\Python39\lib\site-packages\supervised\base_automl.py", line 404, in train_model self.keep_model(mf, model_subpath) File "C:\Users\ZHENGJ\AppData\Local\Programs\Python\Python39\lib\site-packages\supervised\base_automl.py", line 317, in keep_model self.select_and_save_best() File "C:\Users\ZHENGJ\AppData\Local\Programs\Python\Python39\lib\site-packages\supervised\base_automl.py", line 1315, in select_and_save_best self._best_model = min( TypeError: '<' not supported between instances of 'numpy.ndarray' and 'str'
Same issue here. Did you manage to resolve it?
Hi @jiaqizheng2000, @Benjamin-Frost, Could you please provide code to reproduce the issue? Thank you!
automl = AutoML(
ml_task="regression",
train_ensemble=True,
fairness_threshold=0.8,
results_path=resultpath,
model_time_limit=30 * 60,
start_random_models=10,
top_models_to_improve=3,
hill_climbing_steps=3,
golden_features=True,
features_selection=False,
stack_models=True,
explain_level=2,
validation_strategy={
"validation_type": "kfold",
"k_folds": 4,
"shuffle": False,
"stratify": True,}
)
automl.fit(x_train, y_train)
Could you please share dataset as well? or maybe data sample, do you have this error on synthetic data as well?
Thank you! How do you load code and prepare X_train
and y_train
variables?
Simply choose the first column as y_train, and the rest as X_train
@pplonski I Would like to work on this issue
Sure @Rohan581, thanks!