https://github.com/alan-turing-institute/anomaly_with_experts
https://github.com/alan-turing-institute/anomaly_with_experts
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.0%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: alan-turing-institute
- License: mit
- Language: Jupyter Notebook
- Default Branch: master
- Size: 5.45 MB
Statistics
- Stars: 5
- Watchers: 2
- Forks: 4
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Anomaly detection with superexperts under delayed feedback
The visualisation of results from the paper is available here and the analysis of losses and classification metrics is available here. To run the project locally follow the installation instructions below.
Installation
Install anaconda or miniconda https://docs.conda.io/en/latest/miniconda.html.
Clone the repository (note that the flag --recursive is important as the repository contains the submodule NAB):
bash
git clone --recursive https://github.com/alan-turing-institute/anomaly_with_experts.git anomaly_with_experts
cd anomaly_with_experts
Create a conda environment:
bash
conda create -n anomaly_with_experts python=3.7
Activate the environment:
bash
conda activate anomaly_with_experts
Use the package manager pip to install the requirements:
bash
pip install -r requirements.txt
If you do not have Jupyter Notebook installed:
bash
pip install notebook
To launch it:
bash
jupyter notebook
After that, you should first run calculate_predictions.ipynb which calculates the predictions of Fixed-share and Variable-share on NAB and outputs the results.
Then you can run results_analysis.ipynb to analyse the losses and classification metrics and results_plots.ipynb to visualise the plots from the paper. The main functions of the implementation are available in folder anomaly_delays.
Owner
- Name: The Alan Turing Institute
- Login: alan-turing-institute
- Kind: organization
- Email: info@turing.ac.uk
- Website: https://turing.ac.uk
- Repositories: 477
- Profile: https://github.com/alan-turing-institute
The UK's national institute for data science and artificial intelligence.
GitHub Events
Total
- Issues event: 1
Last Year
- Issues event: 1
Issues and Pull Requests
Last synced: 9 months ago
All Time
- Total issues: 1
- Total pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: 1 minute
- Total issue authors: 1
- Total pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- mhauru (1)
Pull Request Authors
- raisadz (1)