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Regular version of the site

Working paper

Machine Learning for Subgroup Discovery under Treatment Effect

arxiv.org. math. Cornell University, 2019. № arXiv:1902.10327.
  In many practical tasks it is needed to estimates effect of a treatemnt on individual level. For example in medicine it is essential to determine the patients that would benifit from a certain medicament. In marketing knowning the persons that are likely to buy a new product would reduce the amount of spam. In this chapter we review the methods to estimate individulize treatment effect from a randomized trial, i.e., an experiment when a part of individuals recieves a new treatment, while the others does not. Finally, it is shown that new efficient methods are needed in this domain.