Comments (5)
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Hello @Mia-3765,
Is it a binary classification problem ? if so, it seems that there is an issue (i am currently fixing it for the next release). Meanwhile, you can try to replace your scoring with the roc_auc from sklearn :
from sklearn.metrics import roc_auc_score
opt = Optimiser(scoring = roc_auc_score, n_folds = 5)
Is it working for you ?
from mlbox.
Hello @Mia-3765, MLBox 0.8.1 has just been released and the issue is now fixed. You can upgrade the package from PyPI :)
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from mlbox.
Hello @Mia-3765
I think I have it. You decided to choose the following parameter :'ne__categorical_strategy':{"search":"choice", "space":[np.NaN]}
which is not possible because it replaces missing values for categorical features by np.NaN which is a float... Try instead : 'ne__categorical_strategy':{"search":"choice", "space":['<NULL>']}
.
If this still doesn't work. Can you tell me if it is a binary or multi class problem ? I can't see your image...
Also have you tried other metrics ? Like accuracy...
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