150 ppt! The most complete "fair perception machine learning and data mining" tutorial, Dr. AIST Toshihiro kamishima, Japan

Address ：https://www.kamishima.net/faml/

The goal of fair sense machine learning or fair sense data mining is to consider fairness while analyzing data 、 discrimination 、 Neutrality and / Or potential problems such as independence .FAML The two main tasks of are unfair detection and unfair prevention . The unfair detection task aims to find unfair treatment in the database . The goal of the unfair prevention task is to learn a statistical model from a potentially unfair data set , Such sensitive characteristics will not affect the results of the model , One of the sensitive features represents information that we hope will not affect the results , Such as social sensitive information or information , Users want to ignore . This article is the most comprehensive 《 Fair perception machine learning and data mining 》 course .