Treffer: CausalML: Python Package for Causal Machine Learning

Title:
CausalML: Python Package for Causal Machine Learning
Authors:
Chen, Huigang, Harinen, Totte, Lee, Jeong-Yoon, Yung, Mike, Zhao, Zhenyu
Publication Year:
2020
Collection:
Computer Science
Statistics
Subject Terms:
Computer Science - Computers and Society, Computer Science - Machine Learning, Statistics - Computation, Statistics - Machine Learning
Document Type:
Report Working Paper
Access URL:
http://arxiv.org/abs/2002.11631
Accession Number:
edsarx.2002.11631
Database:
arXiv

Weitere Informationen

CausalML is a Python implementation of algorithms related to causal inference and machine learning. Algorithms combining causal inference and machine learning have been a trending topic in recent years. This package tries to bridge the gap between theoretical work on methodology and practical applications by making a collection of methods in this field available in Python. This paper introduces the key concepts, scope, and use cases of this package.