bartczernicki/MLDotNet-BaseballClassification
Machine Learning training job using historical baseball data & ML.NET to build a complete set of classifiers.
This project helps baseball analysts and enthusiasts predict future Hall of Fame outcomes for players. By analyzing historical MLB career statistics from 1876-2023, it determines if a batter will appear on the Hall of Fame ballot and whether they will ultimately be inducted. The output is a set of classification models that can be used to evaluate new player careers.
Use this if you are a baseball analyst or historian interested in building and evaluating machine learning models to predict player eligibility and induction into the Hall of Fame based on career statistics.
Not ideal if you are looking for a ready-to-use application for making predictions without any development or model training, as this is a model-building job requiring a .NET development environment.
Stars
15
Forks
4
Language
C#
License
—
Category
Last pushed
Jan 17, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/bartczernicki/MLDotNet-BaseballClassification"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
dotnet/machinelearning-samples
Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.
tghamm/Mistral.SDK
An unofficial C#/.NET SDK for accessing the Mistral AI API
bartczernicki/MachineLearning-BaseballPrediction-BlazorApp
Machine Learning over historical baseball data using latest Microsoft AI & Development...
arafattehsin/SentimentAnalyzer
Fully offline sentiment analysis for .NET with multiple AI engines. Supports 104 languages with...