facebookexperimental / facebookexperimental/Robyn
MMM Calibration
- 主要言語
- Jupyter Notebook
- スター
- 1.5k
- フォーク
- 433
- PR マージ指標
- 30日以内にマージされた PR はありません
説明
While training a model I encountered an issue during model calibration. We initially built a model using 2 years of data and then added synthetic spend data for a media channel over the recent 4 weeks. This channel had 0 contribution earlier, and after adding significant spend data for the last 4 weeks, it still showed 0 contribution.
To address this, we calibrated the model using incremental revenue and spends for the same 4-week period, but the channel continued to show 0 contribution. However, when we increased the training size, we started to see contribution for this media channel.
Could anyone share best practices or insights on how to effectively calibrate the model for recent periods?
@gufengzhou @laresbernardo
コントリビューションガイド
評価
この issue はまだ評価されていません。