goscore
A Go library for scoring machine learning models using PMML, supporting neural networks, decision trees, random forests, and gradient boosted models.
What is goscore?
Goscore is a Go library that implements a scoring API for Predictive Model Markup Language (PMML) files. It allows developers to load machine learning models exported as PMML and use them to make predictions in Go applications, solving the problem of deploying models trained in other ecosystems into production Go services.
Go developers and machine learning engineers who need to deploy pre-trained models (e.g., from R or Python) into Go-based production systems for real-time scoring.
Developers choose Goscore because it provides a lightweight, native Go solution for PMML scoring without external dependencies, supports concurrent scoring for performance, and simplifies the transition from research to production.
Overview
Go Scoring API for PMML
Use Cases
Best For
- Scoring random forest models exported from R in a Go microservice
- Deploying gradient boosted models as part of a real-time prediction API
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