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My clv is coming wrong. It comes negative for many customers. Can you please suggest.

See original GitHub issue
from lifetimes import GammaGammaFitter
ggf = GammaGammaFitter(penalizer_coef = 0)['x'], df['Margin'])
df['clv'] = 0.0
results = {}
results_pnbd_p	= {}
for i in prodname:
    temp= df[df["PROD_MODEL"]==i]
    ggf = GammaGammaFitter(penalizer_coef = 0)['x'], temp['Margin'])
    pnbd = ParetoNBDFitter()
    mod =['x'], temp['t_x'], temp['T'])
    results[i] = mod.params_.values()
      temp['clv'] = ggf.customer_lifetime_value(mod, #the model to use to predict the number of future transactions
                                                      temp['x'], temp['t_x'], temp['T'], temp['Margin'],
                                                      time=12, # months
    print i
    print results
    for j in temp.index:
      df.ix[j,'clv'] = temp['clv'][j]

Issue Analytics

  • State:closed
  • Created 6 years ago
  • Comments:23 (16 by maintainers)

github_iconTop GitHub Comments

vruvoracommented, Dec 11, 2018
CamDavidsonPiloncommented, Nov 12, 2018

Maybe? That means inference elsewhere would suffer. That may be the solution I go with though. I’ll do some testing.

Read more comments on GitHub >

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