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BIRS Workshop Lecture Videos
Controversies in predictive modeling, machine learning, and validation Harrell, Frank
Description
<small>
This talk will cover a variety of controversial and/or current issues related to statistical modeling and prediction research. Some of the topics covered are why external validation is often not a good idea, why validating researchers is often more efficient than validating models, what distinguishes statistical models from machine learning, how variable selection only gives the illusion of learning from data, and advantages of older measures of model performance.
(Presentation 60 min. + Discussion 30 min.)</p>
Item Metadata
Title |
Controversies in predictive modeling, machine learning, and validation
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2019-06-04T13:03
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Description |
<small>
This talk will cover a variety of controversial and/or current issues related to statistical modeling and prediction research. Some of the topics covered are why external validation is often not a good idea, why validating researchers is often more efficient than validating models, what distinguishes statistical models from machine learning, how variable selection only gives the illusion of learning from data, and advantages of older measures of model performance. |
Extent |
87.0 minutes
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Subject | |
Type | |
File Format |
video/mp4
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Language |
eng
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Notes |
Author affiliation: Vanderbilt University
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Series | |
Date Available |
2019-12-02
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0386667
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International