lightweight_mmm
lightweight_mmm copied to clipboard
google
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
https://github.com/google/lightweight_mmm/blob/7aafa2917976891ab7b8cb200c85eacee1afd128/lightweight_mmm/preprocessing.py#L430 `extra_feature_names` need to be changed to `extra_features_names` to align with arguments
How to get contribution for the extra features that is fed into the model?
Seems like the numba _internal module has been changed in a way that broke the decorators module. Not a proper developer myself, so I couldn't track down the more specific...
Hi, I'd love a utility to use a fitted model to generate priors for an update to that same model. Ideally there would be a way to generate the priors...
I am running off of a Google Colab notebook and am trying to follow the code in [this article](https://forecastegy.com/posts/how-to-create-a-marketing-mix-model-with-lightweightmmm/) by Mario Filho. When I try to do `from lightweight_mmm import...
I would love if we could get better flexibility with formatting the plots. For example, being able to rotate the ticks on the x axis would be huge. The project...
In some cases, the performance of these models can be greatly improved with the use of natural log scaling. The current scaling options are restricted to commutative operations like division...
Trying to run a simple example for this in Jupyter: import lightweight_mmm as mmm import pandas as pd # Read in the data from the CSV file data = pd.read_csv('media_mix_data.csv')...
Hi Team, when we use a find_optimal_budgets, how to get the past budget for the n_time_periods vs the newly selected/given budget
Oftentimes I'm finding that the baseline contribution runs down to zero no matter what features or timeline I use for the data. Can anyone help me out on why this...
