INAF.Libraries.Net.ML TECHNICAL REPORT

This solution provides a small .NET class library focused on K-Means clustering over tabular numeric data. The core implementation lives in `INAF.Libraries.Net.ML` and integrates with:- `Microsoft.ML` for model training and prediction- `INAF.Libraries.Net.Data` for matrix-based input structures- `INAF.Libraries.Net.Parallelization` for processor management helpers- `INAF.Libraries.Net.Log` for runtime error logging. The library exposes a simple helper-oriented API that accepts either a file path or an in memory `Matrix` and returns clustering predictions produced by ML.NET. Responsibilities: prepare input data for ML.NET configure and train a K-Means clustering pipeline transform trained model output into strongly typed prediction results validate execution parameters through FluentValidation

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-24
DOI
https://doi.org/10.5281/zenodo.19205428
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

INAF.Libraries.Net.ML TECHNICAL REPORT

Zenodo (CERN European Organization for Nuclear Research)
Parallel Computing and Optimization Techniques
article

INAF.Libraries.Net.ML TECHNICAL REPORT

article en

Abstract

This solution provides a small .NET class library focused on K-Means clustering over tabular numeric data. The core implementation lives in `INAF.Libraries.Net.ML` and integrates with:- `Microsoft.ML` for model training and prediction- `INAF.Libraries.Net.Data` for matrix-based input structures- `INAF.Libraries.Net.Parallelization` for processor management helpers- `INAF.Libraries.Net.Log` for runtime error logging. The library exposes a simple helper-oriented API that accepts either a file path or an in memory `Matrix` and returns clustering predictions produced by ML.NET. Responsibilities: prepare input data for ML.NET configure and train a K-Means clustering pipeline transform trained model output into strongly typed prediction results validate execution parameters through FluentValidation

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 7%
Parallel Computing and Optimization Techniques
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