topic Re: How to get probability score for each prediction from mlflow in Data Engineering

How to get probability score for each prediction from mlflow

Zoumana — Sat, 13 Nov 2021 13:22:34 GMT

I trained my model and was able to get the batch prediction from that model as specified below. But I want to also get the probability scores for each prediction. Do you have any idea?

Thank you!

logged_model = path_to_model

# Load model as a PyFuncModel.

loaded_model = mlflow.pyfunc.load_model(logged_model)

# Predict on a Pandas DataFrame.

import pandas as pd

loaded_model.predict(pd.DataFrame(data))

Re: How to get probability score for each prediction from mlflow

Zoumana — Sat, 13 Nov 2021 15:21:22 GMT

Hi Kaniz,

Great to meet you too!

Thank you for replying to my question.

Best!

Re: How to get probability score for each prediction from mlflow

SyedGhouri — Tue, 08 Nov 2022 19:35:55 GMT

Hi @Kaniz Fatma

Sorry for hijacking the post.

My question is - if I am reading a registered model from mlflow, I can only see the option of .predict method but not .predict_proba.

Do we have any straightforward solution to get the probabilities?

Thanks

Syed

Re: How to get probability score for each prediction from mlflow

SyedGhouri — Tue, 08 Nov 2022 20:06:01 GMT

Hi @Kaniz Fatma

The error said 'PyFuncModel' object has no attribute 'predict_proba'.

As shows above, I was using the following to load the model

loaded_model = mlflow.pyfunc.load_model(logged_model) and got the error.

After going through mlflow documentation, I changed it to

loaded_model = mlflow.sklearn.load_model(logged_model) and it is working fine.

It's all good now. Thanks for your time.

Syed

Re: How to get probability score for each prediction from mlflow

SyedGhouri — Tue, 08 Nov 2022 20:16:31 GMT

Hi @Kaniz Fatma

I do not see the option to select "Best Answer" but feel free to do anything that you think can help this community.

Thanks

Syed

Re: How to get probability score for each prediction from mlflow

OndrejHavlicek — Tue, 08 Aug 2023 08:38:41 GMT

Now you can log the model using this parameter:

mlflow.sklearn.log_model( ..., # the usual params pyfunc_predict_fn="predict_proba" )

which will return probabilities for the first class apparently when using the model for inference (e.g. when loading it using mlflow.pyfunc.spark_udf() ).