mlr

Machine Learning in R for comprehensive model training and evaluation.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is mlr?

The mlr package provides a unified interface to various machine learning algorithms in R. It supports classification, regression, clustering, and survival analysis tasks, making it a powerful tool for data scientists and developers working with R.

Key differentiator

mlr offers a comprehensive, unified interface to various machine learning algorithms in R, making it an ideal choice for researchers and developers who need extensive model evaluation and tuning capabilities.

Capability profile

Strength Radar

Unified interfac…Supports classif…Comprehensive mo…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Unified interface for various machine learning tasks

Supports classification, regression, clustering, and survival analysis

Comprehensive model evaluation and tuning capabilities

Fit analysis

Who is it for?

✓ Best for

Researchers and data scientists who need a comprehensive ML framework in R

Developers working on projects that require extensive model evaluation and tuning capabilities

✕ Not a fit for

Projects requiring real-time machine learning inference

Teams preferring cloud-based managed services for machine learning tasks

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with mlr

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →