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diametrics

DiaMetrics is a web-based educational resource for exploring important concepts regarding binary classification (and its evaluation), which is important in many different fields such as psychodiagnostics (e.g. in determining cut-off values for tests), machine learning or medical testing.

https://github.com/lrosenplaenter/diametrics

Science Score: 67.0%

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
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 2 DOI reference(s) in README
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    Academic publication links
    Links to: zenodo.org
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    Academic email domains
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (13.9%) to scientific vocabulary

Keywords

binary-classification binary-classification-evaluation learning-by-doing learning-resources learning-tool sensitivity specificity teaching-materials teaching-tool
Last synced: 6 months ago · JSON representation ·

Repository

DiaMetrics is a web-based educational resource for exploring important concepts regarding binary classification (and its evaluation), which is important in many different fields such as psychodiagnostics (e.g. in determining cut-off values for tests), machine learning or medical testing.

Basic Info
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Topics
binary-classification binary-classification-evaluation learning-by-doing learning-resources learning-tool sensitivity specificity teaching-materials teaching-tool
Created over 2 years ago · Last pushed 12 months ago
Metadata Files
Readme License Citation

README.md

DiaMetrics

DiaMetrics is a web-based educational resource for exploring important concepts regarding binary classification (and its evaluation), which is important in many different fields such as psychodiagnostics (e.g. in determining cut-off values for tests), machine learning or medical testing.

DOI

Installation & Usage

No installation is necessary. Open DiaMetrics directly. Alternatively: Simply download and open index.html in your browser or store all files on your web server.

If you actually publish DiaMetrics elsewhere (e.g. on your website, in another project, etc.), I would be happy to be notified!

The tutorial can easily be deactivated in index.js by setting the showtutorialvar variable (ln 9) to false. The data displayed in example 2 is defined by data.js, and not generated pseudo-randomly (as in examples 1 & 3).

Versions

There are two other versions of DiaMetrics:

  • DiaMetrics_DE (web | repository) is the German version of DiaMetrics.
  • DiaMetrics_lite (web | repository) is a reduced version of DiaMetrics that can be used, for example, in presentations or to engange with an audience.

Contributing

If you have found any bug or typo (or anything else that doesn't seem right) in DiaMetrics, I would be happy to be notified directly. You can also open an issue on github.

Note: Issues and pull requests are not actively monitored on a regular basis.

Authors, citation and acknowledgments

DiaMetrics was developed by Leon Rosenplnter for teaching at the Department of Psychological Diagnostics (Prof. Dr. Martin Kersting), Justus-Liebig-University Giessen, Germany. Many thanks to S. Bender and D. Bonarius for their essential feedback and corrections, greatly improving this project.

Please quote DiaMetrics as follows: See CITATION.md

DiaMetrics uses Bootstrap v5.3.1 for the design of the website and some visual functions.

DiaMetrics uses Chart.js v4.4.0 to display the scatter plots.

DiaMetrics uses the dragdata plugin for Chart.js v2.2.3 to make the separator draggable.

License

Copyright (c) 2023 - 2025 Leon Rosenplnter. DiaMetrics is available under the MIT license. The full text of the license can be found in the LICENSE file.

Owner

  • Login: lrosenplaenter
  • Kind: user

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: DiaMetrics
message: >-
  If you mention, use, adapt or publish this project
  elsewhere, please cite it using the metadata from this
  file.
type: software
authors:
  - given-names: Leon
    family-names: Rosenplänter
    orcid: 'https://orcid.org/0009-0001-4961-2281'
identifiers:
  - type: doi
    value: 10.5281/zenodo.15002679
    description: Zenodo Archive
repository-code: 'https://github.com/lrosenplaenter/DiaMetrics'
url: 'https://lrosenplaenter.github.io/DiaMetrics'
abstract: >-
  DiaMetrics is a web-based educational resource for
  exploring  important concepts regarding binary
  classification (and its  evaluation), which is important
  in many different fields  such as psychodiagnostics (e.g.
  in determining cut-off  values for tests), machine
  learning or medical testing.
keywords:
  - specificity
  - sensitivity
  - learning-by-doing
  - binary-classification
  - binary-classification-evaluation
  - teaching-materials
  - teaching-resources
  - teaching-tool
  - learning-materials
  - learning-resources
  - learning-tool
license: MIT
commit: v1.0.1
version: 1.0.1
date-released: '2025-03-10'

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