Minyus / causallift

CausalLift: Python package for causality-based Uplift Modeling in real-world business

https://causallift.readthedocs.io/

Minyus/causallift Issues

Getting Json Formatter error
Updated 2 years ago1
XGBooster Invalid missing value: null
Updated 2 years ago1
pipeline issue (Kedro?)
Updated 2 years ago1
TypeError: run() missing 1 required positional argument: 'hook_manager'
Closed 2 years ago2
ValueError: Input contains NaN, infinity or a value too large for dtype('float64').
Closed 2 years ago2
A question about train.df and test.df
Closed 2 years ago1
How do we can give separtae scale_pos_weight for two separated models?
Closed 4 years ago1
Examples with Observational data
Closed 4 years ago2
Question Code & Result
Closed 4 years ago6
Error regarding to base_score
Closed 4 years ago2
Some clarification about the code
Closed 4 years ago14
cl.estimate_cate_by_2_models() does not work with XGBoost version 1.0.2
Closed 4 years ago4
Is there a causal modeling for multiple treatments?
Closed 4 years ago5
Order of features in train and new data
Closed 4 years ago5
Handle imbalance
Closed 4 years ago10
CATE vs Propensity
Closed 4 years ago5
The effect of Stratify = ['Treatment']
Closed 4 years ago3
A clear explanation
Closed 4 years ago1
Using Causallift for later predition
Closed 4 years ago23
Generated data are random data?
Closed 4 years ago3
The robustness of uplift
Closed 4 years ago1
estimate_cate_by_2_models crashes when col_propensity is provided in the data and enable_ipw=False
Closed 5 years ago1