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This repository has been archived by the owner on Jul 21, 2024. It is now read-only.
It's been a longstanding issue in the legacy Lifetimes library that the plot_calibration_purchases_vs_holdout_purchases function in plotting.py cannot be used without first running data through calibration_and_holdout_data in utils.py. This is a useful plotting function for model evaluation, but for those of us working with huge volumes of transaction data, utils.py just isn't going to cut it and the RFM aggregations must be done in a separate service like Spark or Snowflake, effectively blocking the use of this function.
Replacing the calibration_holdout_matrix argument with separate calibration_matrix and holdout_matrix arguments should be enough to resolve this matter.
The text was updated successfully, but these errors were encountered:
It's been a longstanding issue in the legacy Lifetimes library that the
plot_calibration_purchases_vs_holdout_purchases
function inplotting.py
cannot be used without first running data throughcalibration_and_holdout_data
inutils.py
. This is a useful plotting function for model evaluation, but for those of us working with huge volumes of transaction data,utils.py
just isn't going to cut it and the RFM aggregations must be done in a separate service like Spark or Snowflake, effectively blocking the use of this function.Replacing the calibration_holdout_matrix argument with separate calibration_matrix and holdout_matrix arguments should be enough to resolve this matter.
The text was updated successfully, but these errors were encountered: