imesc
This app is intended to dynamically integrate machine learning techniques to explore multivariate data sets.
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○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 (15.4%) to scientific vocabulary
Keywords
Repository
This app is intended to dynamically integrate machine learning techniques to explore multivariate data sets.
Basic Info
Statistics
- Stars: 9
- Watchers: 1
- Forks: 2
- Open Issues: 1
- Releases: 10
Topics
Metadata Files
README.md
iMESc: Interactive Machine Learning App for Environmental Sciences
iMESc is a state-of-the-art application designed to bring the power of machine learning to environmental science. Through its interactive interface, it facilitates a more intuitive and seamless experience for users to engage with complex data sets and analysis processes.
Installation & Usage
Option 1: Running iMESc in RStudio
Step 1: Install R and RStudio
If you haven't already, install R and RStudio by following the instructions on their respective websites.
Step 2: Open RStudio
Once R and RStudio are installed, open RStudio.
Step 3: Install Shiny Package
Install the shiny package if it's not already installed. You can do this by running the following command in the RStudio console:
r
install.packages('shiny')
Step 4: Run iMESc
To start using the iMESc app, run the following code in the RStudio console:
r
shiny::runGitHub('iMESc','DaniloCVieira', ref='main')
Note: When you use the iMESc app for the first time, it will automatically install all the necessary packages, which may take several minutes to complete. However, once the first installation is finished, subsequent access of the app will be much faster. If the required packages are not already loaded, they typically take several seconds to load. On the other hand, if the packages are already loaded, iMESc will start almost instantly.
Option 2: Running iMESc with Docker
For a hassle-free setup, especially for users unfamiliar with RStudio, iMESc is available as a Docker container. The Docker image includes all dependencies, ensuring a consistent environment for running iMESc.
Prerequisites
- Install Docker by following the instructions for your operating system on the Docker website.
Run the Docker Image
bash
docker pull vieiradc/imesc
docker run -d -p 3838:3838 vieiradc/imesc
Access the App
Once the container is running, open your browser and navigate to:
http://localhost:3838
Documentation and User Manual
For detailed guidance on how to format your data and use the app with custom datasets, please refer to the iMESc User Manual.
The manual provides step-by-step instructions and examples to ensure you can easily prepare your data and fully utilize the app's capabilities.
License
This project is licensed under the CC BY-NC-ND 4.0 license. To view a copy of this license, visit CC BY-NC-ND 4.0.
Owner
- Login: DaniloCVieira
- Kind: user
- Repositories: 5
- Profile: https://github.com/DaniloCVieira
Citation (citation.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: >-
iMESc: An Interactive Machine Learning App for
Environmental Science
message: >-
Please cite this software using the metadata from
'preferred-citation'.
type: software
authors:
- given-names: Danilo Cândido
family-names: Vieira
email: vieiradc@yahoo.com.br
orcid: 'https://orcid.org/0000-0002-7989-6553'
affiliation: Universidade Federal de São Paulo
- orcid: 'https://orcid.org/0000-0001-8625-4279'
given-names: Gustavo
family-names: Fonseca
email: gfonseca.unifesp@gmail.com
affiliation: Universidade Federal de São Paulo
version: 2.1.0.1
date-released: '2022-11-03'
url: 'https://github.com/DaniloCVieira/iMESc'
doi: 10.5281/zenodo.7278042
GitHub Events
Total
- Create event: 1
- Issues event: 1
- Release event: 1
- Watch event: 5
- Push event: 33
- Fork event: 2
Last Year
- Create event: 1
- Issues event: 1
- Release event: 1
- Watch event: 5
- Push event: 33
- Fork event: 2
Dependencies
- R >= 3.5.0 depends
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