lightweight_mmm
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google
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
Precision formatting was done using an outdated method causing an error in pandas.
**Description:** After setting up a new conda environment and installing the `lightweight_mmm` package, I encountered a `RuntimeError` when attempting to import the `optimize_media` function. **Steps to Reproduce:** - Create a...
Hello! I'm wondering if there is a fix to a faulty Adstock `lag_weight` parameter that is learned in my MMM. I'm using the `hill_adstock` function with some holiday features as...
Hi team - I am building a MMM model with 8 channels and 2 extra features. It is a geo model at US state level (51 geos). It takes couple...
Hi, I am a MMM scientist and currently using LightWeightMMM for my job. We are passing the model our knowledge of lift tests for specific medias that we have tested....
Hello, In the predict function in lightweight-mmm module, there is this code: ``` if media_gap is not None: if media.ndim != media_gap.ndim: raise ValueError("Original media data and media gap must...
If you read [example](https://github.com/google/lightweight_mmm/blob/bb1c1a898b7411d50be54353fa94570caf373572/examples/simple_end_to_end_demo.ipynb#L1328) and [code](https://github.com/google/lightweight_mmm/blob/bb1c1a898b7411d50be54353fa94570caf373572/lightweight_mmm/optimize_media.py#L276), then the budget is media data (impressions and clicks, for example). But shouldn't it be advertising costs?
(Correct me if I am wrong..) Currently adstock transformation normalization is performed in media_transforms/adstock via: `lambda adstock_values: adstock_values / (1. / (1 - lag_weight)` However I believe this is the...
Hi, I have just been playing with Lightweight for a week or so, only with the example notebooks. I have encountered two "issues" and I wonder whether these are expected...
