Comments (1)
anantp316
commented on June 11, 2024
Here are the following checks you may need to do.
- Importing
matplotlib.pyplot as plt. - Importing the following statement
from lightweight_mmm import plot - Try adding a semi-colon at the end of your mentioned plot statements.
If nothing works, try doing a clean install of the lightweight_mmm library and use the git link mentioned in the example notebook (or in the ReadME) to re-install the library.
from lightweight_mmm.
Related Issues (20)
- How can I input future media_data_test for optimization in upcoming periods? HOT 1
- How can channel-wise optimized conversions be obtained?
- Extra features
- Addressing Heteroscedasticity
- Geo level attribution and response curves
- Budget Allocation Percentage breakdown by channel HOT 10
- Question on tensorflow requirement
- Dtype object is not a valid JAX array type. Only arrays of numeric types are supported by JAX. HOT 5
- Same pre-optimization and post-optimization channel budget allocation ratios , but suggesting much higher budget instead of aligning the budget to the one i requested. HOT 10
- Paid Search bias - Nested model
- Divergences and n_eff
- Outliers and influential points
- budget allocator: How to set up lower bound and upper bound per channel?
- add got incompatible shapes for broadcasting: (95,), (90,). HOT 5
- TypeError: add got incompatible shapes for broadcasting: (58,), (54,). HOT 8
- Negative Values in Pre optimization predicted Target vs Post optimization predicted Target
- Budget Optimization
- RuntimeError: Cannot find valid initial parameters. Please check your model again.
- TypeError: where() got some positional-only arguments passed as keyword arguments: 'condition, x, y' HOT 6
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from lightweight_mmm.