Open shadiakiki1986 opened 6 years ago
can you provide steps to reproduce?
The steps are just the default model = Mljar(...)
followed by model.fit(...)
.
Here is the exact code
model = Mljar(
project='g2-ml take2/ex3',
#experiment='Get 0.58 A',
experiment='RF enc-on-raw A',
metric='auc',
algorithms=['rfc'],
validation_kfolds=15,
validation_shuffle=False,
validation_stratify=True,
validation_train_split=None,
tuning_mode='Sport',
create_ensemble=True,
single_algorithm_time_limit='10'
)
model.fit(train_features, train_target)
It seems that this was related to #8 where my target was accidentally continuous whereas the experiment was a binary classification. Feel free to close this issue
Hello. When I call
fit
from the mljar python API, it fails with the following status on each of the experiments:Status details: Error : Unknown label type: continuous
Edit: also, the
fit
call just hangs without returning any error