자료유형  

 학위논문

Control Number  

0016934531

International Standard Book Number  

9798380470537

Dewey Decimal Classification Number  

658.403

Main Entry-Personal Name  

Seiler, Benjamin B.

Publication, Distribution, etc. (Imprint  

[S.l.] : Stanford University., 2023

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2023

Physical Description  

1 online resource(96 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-04, Section: A.

General Note  

Advisor: Palacios, Julia;Taylor, Jonathan;Art, Art.

Dissertation Note  

Thesis (Ph.D.)--Stanford University, 2023.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약Model-agnostic feature importance measures are central to the task of demystifying opaque or "black-box" machine learning models. The proliferation of such models within highstakes decision making settings such as healthcare or banking necessitates the development of flexible and trustworthy approaches to the problem. With no ground truth feature importance to compare to, competing methods provide contrasting approaches and/or philosophies often with a claim of superiority. Some of the most popular recent approaches are adaptations of tools from cooperative game theory used in reward or cost sharing problems. In this document, we report on recent advances among such feature importance methods. In particular, we discuss a "data-centric" cohort-based framework for modelagnostic local feature importance using Shapley values. We propose a primary importance measure and explore several adaptations of that method better suited for specific use cases or data regimes. We analyze the properties and behaviors of these methods and apply them to a broad range of synthetic and real-world problem settings including voter registration and recidivism data. We then propose and discuss new methods for local importance aggregation and feature importance evaluation.

Subject Added Entry-Topical Term  

Game theory.

Subject Added Entry-Topical Term  

Swimming pools.

Subject Added Entry-Topical Term  

Recidivism.

Subject Added Entry-Topical Term  

Information theory.

Subject Added Entry-Topical Term  

Voters.

Subject Added Entry-Topical Term  

Decision making.

Subject Added Entry-Topical Term  

Symmetry.

Subject Added Entry-Topical Term  

Applied mathematics.

Subject Added Entry-Topical Term  

Recreation.

Subject Added Entry-Topical Term  

Theoretical mathematics.

Added Entry-Corporate Name  

Stanford University.

Host Item Entry  

Dissertations Abstracts International. 85-04A.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:642244