INAF.Libraries.Net.ML TECHNICAL REPORT
Year: 2026
Type: article
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
Author: Carraro, Francesco
Institution: National Institute for Astrophysics
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7140225225
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