error tu run btyd model

[chagoo]

I run the model in april and ok but today I need run the model and I have error and it is not possible continue 

I change the penalizer_coef and nothing 

# fit a model with a larger penalizer coefficient

bgf_engagement = BetaGeoFitter(penalizer_coef=100000.0)  # Increase the penalizer coefficient

bgf_engagement.fit(

    bg_training_data['frequency_cal'],

    bg_training_data['recency_cal'],

    bg_training_data['T_cal']

)

message: Desired error not necessarily achieved due to precision loss. success: False status: 2 fun: -22.17548856616192 x: [-6.111e+00 -1.005e+01 -1.339e+01 -8.842e+00] nit: 84 jac: [ 2.953e-04 -1.193e-03 4.319e-04 5.391e-04] hess_inv: [[ 5.006e-01 -1.666e-01 -5.504e-01 -2.107e-01] [-1.666e-01 1.067e+02 1.749e+02 9.615e+01] [-5.504e-01 1.749e+02 3.339e+02 1.197e+02] [-2.107e-01 9.615e+01 1.197e+02 1.170e+02]] nfev: 135 njev: 123

ConvergenceError: The model did not converge. Try adding a larger penalizer to see if that helps convergence.

File <command-2995118494231631>, line 3 1 # fit a model with a larger penalizer coefficient 2 bgf_engagement = BetaGeoFitter(penalizer_coef=100000.0) # Increase the penalizer coefficient ----> 3 bgf_engagement.fit( 4 bg_training_data['frequency_cal'], 5 bg_training_data['recency_cal'], 6 bg_training_data['T_cal'] 7 )

[Kaniz_Fatma]

Hi @chagoo,To fix this, try lowering the penalizer coefficient, checking the data quality for anomalies, scaling the data, increasing the number of iterations, or experimenting with different initial parameters. These steps should help resolve the convergence issue. Let me know if you need further assistance or if there’s anything else I can help with!