MLApp technical Report

Fuente: Zenodo
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Bibliographische Detailangaben
1. Verfasser: Carraro, Francesco
Format: Recurso digital
Sprache:Englisch
Veröffentlicht: Zenodo 2026
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_version_ 1866901755749466112
author Carraro, Francesco
author_facet Carraro, Francesco
contents <p><strong>MLApp </strong>solution is a `.NET 10` machine-learning workflow centered on a console application and a set of supporting class  libraries.<br>Its primary purpose is to:</p> <ul> <li>read scientific or tabular input data</li> <li>validate runtime configuration</li> <li>run K-Means clustering through `ML.NET`</li> <li>generate grouped output artifacts</li> <li>publish an HTML report with optional map visualization</li> </ul> <p>The solution is structured as a thin executable layer plus reusable internal libraries for data handling, reading, ML execution, output writing, localization, and parallelization</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19202939
institution Zenodo
language eng
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle MLApp technical Report
Carraro, Francesco
ML
App
.NET
Console App
Clustering
K-means
<p><strong>MLApp </strong>solution is a `.NET 10` machine-learning workflow centered on a console application and a set of supporting class  libraries.<br>Its primary purpose is to:</p> <ul> <li>read scientific or tabular input data</li> <li>validate runtime configuration</li> <li>run K-Means clustering through `ML.NET`</li> <li>generate grouped output artifacts</li> <li>publish an HTML report with optional map visualization</li> </ul> <p>The solution is structured as a thin executable layer plus reusable internal libraries for data handling, reading, ML execution, output writing, localization, and parallelization</p>
title MLApp technical Report
topic ML
App
.NET
Console App
Clustering
K-means
url https://doi.org/10.5281/zenodo.19202939