Implementation of the core idea behind the DeepIV paper, but with tree boosting and quantile regression instead of deep learning and mixtures of gaussians.
- for more in depth discussion, see this blog post http://jmarkhou.com/npiv/
- look at
Run via docker:
How to build:
- dockerfile just installs the package via pip with the -e option, and docker-compose then mounts this directory to that install location, so that any changes made are directly reflected. Thus, just run the container, and make whatever changes as you like.
- to run tests as you develop, do
docker exec 270033469fd0 pytest -s, excep with whatever the hash of the container is (do
docker container ls to see running containers)
- or even better, just use bash in the container:
docker exec 270033469fd0 bash