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UBC Theses and Dissertations
Transporting and evaluating predictive models in different environments Farahani, Melika
Abstract
In many data-driven applications, transporting a model from one environment to another has always been challenging. When experiments are conducted on a specific location or population, the problem of whether the results can be applied to a new location or population arises. The majority of the work in this area assumes that some conditional probabilities are transportable, even though they can be affected by unmeasured variables. We propose methods for transporting predictive models learned in a source population to target when we have limited information about the target population. These methods can cancel out the effect of the unmeasured variables using the ratio of conditional probabilities. We test the proposed methods using forest fire and stroke datasets.
Item Metadata
| Title |
Transporting and evaluating predictive models in different environments
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| Creator | |
| Supervisor | |
| Publisher |
University of British Columbia
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| Date Issued |
2022
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| Description |
In many data-driven applications, transporting a model from one environment to another has always been challenging. When experiments are conducted on a specific location or population, the problem of whether the results can be applied to a new location or population arises. The majority of the work in this area assumes that some conditional probabilities are transportable, even though they can be affected by unmeasured variables. We propose methods for transporting predictive models learned in a source population to target when we have limited information about the target population. These methods can cancel out the effect of the unmeasured variables using the ratio of conditional probabilities. We test the proposed methods using forest fire and stroke datasets.
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| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2022-08-30
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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 |
10.14288/1.0418465
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| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2022-11
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| Campus | |
| Scholarly Level |
Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International