#Tutorial on BDT reweighter
We are considering reweighting problem (introduction to this problem can be found in the post) and show how parameters of classifier/regressors tuning affects on the reweighting rule reconstruction.
Tutorial notebook consists of several parts:
- Neural network parameters: demonstration how these parameters influence reweighting rule;
- Variance and bias errors discussion
- BDT reweighter tuning
- real use-case in high energy physics (HEP): reweighting problem for sPlot data, when weights (that can be negative) are defined for the target distribution.