---
title: Debiased/Double Machine Learning (DML)
url: https://www.emergentmind.com/topics/debiased-double-machine-learning-dml
type: topic
---

# Debiased/Double Machine Learning (DML)

Double/Debiased Machine Learning (DML) is a general framework for the construction of estimators for low-dimensional parameters of interest—such as average treatment effects (ATE) or coefficients in structural econometric models—in the presence of high-dimensional or complex nuisance functions. DML achieves valid inference by combining Neyman-orthogonal moment functions and K-fold cross-fitting, allowing arbitrary flexible machine learning (ML) methods for nuisance estimation while preserving root-n consistency and asymptotic normality for the parameter of interest. The methodology

Source: https://www.emergentmind.com/topics/debiased-double-machine-learning-dml