Closed orydatadudes closed 1 year ago
Same problem!
Hi @orydatadudes, @Jaspernwd - this issue can be quite difficult to debug, as it stems from the sampling process of the underlying pymc3
library. It generally has to do with how you initialize the underlying prior distribution when using bayesian methods. If you don't explicitly model the distribution yourself, autoimpute
tries to do it for you, but that doesn't always work.
i got the above error when trying to use autoimpute on data frame with two columns from kaggle india air quality data
df[['NO', 'NO2'].head() NO NO2 0 0.48 13.58 1 0.77 25.43 2 5.35 44.17 3 23.23 47.66 4 43.73 45.93
df[['NO', 'NO2']].dtypes: NO float64 NO2 float64
np.isnan(df[['NO', 'NO2']]).sum() NO 1948 NO2 836
i also try taking N rows from df so maybe i could find the rows that responsible to the problem: when i took top 10820 rows it work when i took took top 10825 it didn't work when i tool rows from 10810-10830 it work
what is the problem and what should i do thanks