predict_proba does not return probabilities after load_model in VerticaPy >= 1.0.5

[mail4umar]

Discussed in #1351

^{Originally posted by okankcb July 3, 2025}
Hello,

We encountered an issue using predict_proba after calling load_model in VerticaPy versions 1.0.5 and 1.1.1.

After loading a saved model using load_model, calling predict_proba executes without error, but does not return the expected probability columns.

Work fine in :

• VerticaPy 0.12

Issue reproducible in :

• Verticapy 1.0.5
• Verticapy 1.1.1

Reproducible example with VerticaPy 1.0.5 and 1.1.1 :

from verticapy.machine_learning.vertica import RandomForestClassifier
drop(name = schema +".model_titanic_test_rfc", method = "model")
model = RandomForestClassifier(name = schema +".model_titanic_test_rfc")
model.fit(titanic,["age","fare"], "survived")

from verticapy.machine_learning.vertica.model_management import load_model
model=load_model(schema + ".model_titanic_test_rfc")

model.predict_proba(titanic, 
                    X = ["age","fare"],
                    name = "predict_proba")

As a temporary solution while waiting for a fix, saving and loading the model using Python's pickle library works correctly. Example :

import pickle
from verticapy.machine_learning.vertica import RandomForestClassifier

drop(name = schema + ".model_titanic_recette_test_rfc", method = "model")
model = RandomForestClassifier(name = schema + ".model_titanic_recette_test_rfc")
model.fit(titanic_recette, ["age", "fare"], "survived")

with open("model_titanic_rfc.pkl", "wb") as f:
    pickle.dump(model, f)

with open("model_titanic_rfc.pkl", "rb") as f:
    model_loaded = pickle.load(f)

model_loaded.predict_proba(titanic_recette, ["age", "fare"])

Please let us know if :

• A specific parameter must be set to return the probability columns after load_model
• Or if a fix or patch is planned

Best regards,

Okan Kocabiyik