ps_minimal_showcase
This repo contains a working example of the methodology I've proposed in my paper "Mining Potentially Explanatory Patterns via Partial Solutions".
Science Score: 57.0%
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Low similarity (8.9%) to scientific vocabulary
Repository
This repo contains a working example of the methodology I've proposed in my paper "Mining Potentially Explanatory Patterns via Partial Solutions".
Basic Info
- Host: GitHub
- Owner: Giancarlo-Catalano
- Language: Python
- Default Branch: master
- Size: 8.45 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
This repository is a working code example of the system being described in the paper "Mining Potentially Explanatory Patterns via Partial Solutions", which you can find here
The system defines the following components: * PS: a partial solution * (essentially a wrapper over a numpy array of integers, where * is represented by -1) * PSMiner: The algorithm which searches for nice PSs using a reference population * (used to obtain a PS Catalog, which is just a list of PSs) * PickAndMergeSampler: The algorithm which samples from the PS Catalog to obtain "full" solutions
For your convenience, there's also a lengthy list of Benchmark problems for you to try.
(To run this script, you'll need Python 3.10 or later, and to have the following installed: * numpy * scikit-learn * scipy (for the optional BivariateANOVALinkage.py)
In case you're struggling to understand the code, here are some descriptions of the classes: * PRef: The reference population, packaged into a convenient object which includes both the solutions and their fitnesses * FS / FullSolution: A wrapper for numpy arrays of integers * SearchSpace: Represents the combinatorial search space we are searching in * EvaluatedPS / EvaluatedFS: data structures used to include the fitness value with PSs/FSs * Metric: An object used to evaluate a PS, eg Simplicity, MeanFitness, Atomicity * There are a lot of them to be used, and note that you may replace Atomicity with Linkage etc..
Owner
- Name: Giancarlo Catalano
- Login: Giancarlo-Catalano
- Kind: user
- Location: Stirling
- Company: University of Stirling
- Repositories: 2
- Profile: https://github.com/Giancarlo-Catalano
MPhil CS student at the University of Stirling, working on XAI.
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Catalano
given-names: Giancarlo
orcid: https://orcid.org/0009-0000-6504-2541
title: "PS Assisted Explainability"
version: 1.0.0
identifiers:
- type: doi
value: 10.1145/3638530.3654318
date-released: 2024-04-05