[Iefac.list] IISE-DAIS webinar on this Friday

[Zimo Wang]

Greetings!

This is Zimo Wang from Binghamton University. I would like to share the
information about the upcoming IISE-DAIS webinar with the community. Thank
you so much for your help!

regards,
Zimo


=================

Dear Colleagues,

Here is a kind reminder of the upcoming IISE-DAIS webinar on this
Friday. This DAIS
(Data Analytics & Information Systems) webinar essentially brings together
members from academia, industry and government who share a common interest
in topics related to research and practice of data analytics and
information systems, promoting its applications in the emerging areas.

Our next webinar is scheduled on March, 26th, 2021. Our guest speaker would
be Dr. Daniel Apley from Northwestern University. The detailed information
is listed below:


*Date:* Friday, March 26, 2021

*Time:* 11:00 am ET

*Registration Link:* https://zoom.us/j/91950616389

*Abstract*

In many supervised learning applications, understanding and visualizing the
effects of the predictor variables on the predicted response is of
paramount importance. A shortcoming of black box supervised learning models
(e.g. complex trees, neural networks, boosted trees, random forests,
nearest neighbours, local kernel-weighted methods and support vector
regression) in this regard is their lack of interpretability or
transparency. Partial dependence plots, which are the most popular approach
for visualizing the effects of the predictors with black box supervised
learning models, can produce erroneous results if the predictors are
strongly correlated. This talk discusses a new visualization approach,
accumulated local effects (ALE) plot, which does not require this
unreliable extrapolation with correlated predictors. It is substantially
less computationally expensive and avoids the extrapolation problem that
can render PD plots unreliable when the predictors are highly correlated.

*Biography*

Dr. Daniel Apley is currently a professor of Industrial Engineering and
Management Sciences at Northwestern University. He obtained B.S., M.S., and
Ph.D. degrees in Mechanical Engineering and an M.S. degree in Electrical
Engineering from the University of Michigan. His research interests lie at
the interface of engineering modeling, statistical analysis, and predictive
analytics, especially with large and complex data structures. Dr. Apley’s
work has been supported by numerous industries and government agencies. He
received the NSF CAREER award, the IIE Transactions Best Paper Award, and
the Wilcoxon Prize for best practical application paper appearing in
Technometrics. He has served as the Editor-in-Chief for Technometrics
<http://amstat.tandfonline.com/loi/tech#.VqFRGfkrJhE> and the Journal of
Quality Technology <http://asq.org/pub/jqt/>, Chair of the Quality,
Statistics & Reliability Section of INFORMS, and Director of the
Manufacturing and Design Engineering Program at Northwestern.

Enclosed please find the detailed information about this webinar. Please
feel free to share this announcement with your colleagues/students/research
scholars/others. Thank you!
=================



-- 
Zimo Wang, Ph.D.,
Assistant Professor,
Department of Systems Science and Industrial Engineering (SSIE),
State University of New York at Binghamton
Office: EB-J16
Tel.: 607-777-5012
E-mail: zimowang at binghamton.edu
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