Fidelity Assessment for Model Selection
Project description
FAMS : Fidelity Assessment for Model Selection
Author : Adam Cox, PhD
Contact : adam.cox@asdl.gatech.edu
Capabilities
Expert-driven ranking of items
This was originally developed the rank the fidelity of models via ranked ordering in terms of the resolution, abstraction, and scope of the given models.
This has been expanded to provide the capability to perform a similar assessment for a list of generic items, such as a list of technologies.
Input
For each metric, the users provide a set of ranked orders to designate whether each item is better/worse/equivalent to each other item
Outputs
- Main output: For each item, a score based on the probability that item is the best of the set
- Other outputs:
- Probability of second, third, ..., last
- Notional distribution using KDE based on expert-provided samples
For Models
Model data-driven correction of fidelity scores
Fidelity - Efficiency Multi-Attribute Scoring and Decision-Making
For more information see Adam's dissertation
Changelog
v1.1.1: Minor bug fix version
See commit message, multiple minor bug fixes
v1.1: Method generalization, usability features
Create generalized Ranking object and differentiate from ModelRanking object in order to be able to use expert-driven data processing to assess more generic items such as technologies in addition to just models.
Other updates:
- Updated parameters such as description, category
- Capability to store/load rankings in JSON files, including processed probabilities
- Updated examples and plotting
- New TOPSIS method
- Progress bars
Project details
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