tree
Classification and regression trees for R.
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is tree?
The tree package provides functions to create classification and regression trees in R. It is a powerful tool for predictive modeling, allowing users to build decision trees that can be used for both categorical and continuous outcomes.
Key differentiator
“The tree package stands out by offering a straightforward and efficient way to build classification and regression trees in R, making it an essential tool for predictive modeling tasks within the R ecosystem.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Researchers and analysts who need to build classification or regression trees for predictive analytics.
Educators teaching machine learning concepts, particularly decision trees in R.
✕ Not a fit for
Projects requiring real-time predictions as the package is designed for batch processing.
Large-scale data sets where computational efficiency is critical.
Cost structure
Pricing
Free Tier
None
Starts at
See website
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with tree
Step-by-step setup guide with code examples and common gotchas.