https://github.com/adityalab/ratss
https://github.com/adityalab/ratss
Last synced: 28 days ago
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- Host: GitHub
- URL: https://github.com/adityalab/ratss
- Owner: AdityaLab
- Created: 2021-07-16T22:03:07.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2021-11-02T01:42:22.000Z (over 3 years ago)
- Last Synced: 2023-10-26T11:54:17.520Z (over 1 year ago)
- Language: Python
- Size: 4.6 MB
- Stars: 2
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 'Actionable Insights in Multivariate Time-series for Urban Analytics', Anika Tabassum, Supriya Chinthavali, Varisara Tansakul, and B. Aditya Prakash
==========================================================================
Paper:
-------------
Both paper and supplementary readings are added here. Check Ratss_SigKDD2021_MILETS.pdf
-------------
Usage:
Note: You need to set the correct MATLAB_path in the makefile (Including the MATLAB executable).
```
- Example:
MATLAB_path = '/usr/local/bin/./matlab'
```
To run Ratss for sample data do as follows,
```
>> make demo
```
'make demo' will run for the sample data (Covid-19 interventions data in the paper) in data/ directory.
Output:
-------
#located in result_file directory
-- covid_interventions_exp.csv: nXs contains the rationalization weight of n time-series in s segments in the segment file.
-- covid_interventions_ei.csv: nXs, each column contains the time-series index ranked by rationalization weights in _exp.csv for each segment in the segment file.
-- covid_interventions_Prest.txt: file of n, contains cost Prest of n time-series
-- covid_interventions_ttl_path.txt: contains value of ttl path of the constructed segment graph, i.e., K
-- covid_interventions_B.txt: file of nX3, contains cost K*PB-PRest,PB,Prest of n time-series
Citations:
------------
This paper is under creative common license. If you use our code and paper use the following citations.
@article{tabassum2021actionable,
title={Actionable Insights in Multivariate Time-series for Urban Analytics},
author={Tabassum, Anika and Chinthavali, Supriya and Tansakul, Varisara and Prakash, B Aditya},
journal={7th International Workshop of Mining and Learning Time Series in ACM SigKDD},
year={2021}
}