Scikit-Survival

Survival analysis built on top of scikit-learn for Python.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is Scikit-Survival?

scikit-survival is a Python module that extends the capabilities of scikit-learn to include survival analysis, allowing users to perform advanced statistical analyses while leveraging familiar machine learning workflows and tools.

Key differentiator

Scikit-Survival stands out by providing specialized survival analysis capabilities directly within the popular scikit-learn framework, offering seamless integration with existing machine learning pipelines.

Capability profile

Strength Radar

Survival analysi…Integration with…Supports various…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Survival analysis built on top of scikit-learn

Integration with scikit-learn for preprocessing and cross-validation

Supports various survival models including Cox proportional hazards model

Fit analysis

Who is it for?

✓ Best for

Researchers needing to perform survival analysis within a familiar scikit-learn framework

Projects requiring integration with existing scikit-learn workflows for preprocessing and validation

✕ Not a fit for

Developers looking for a cloud-based service for survival analysis

Teams preferring proprietary software over open-source solutions

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 Scikit-Survival

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

View Setup Guide →