TPOT

Spec sheet

Purpose

TPOT is a Python automated machine learning tool that optimizes machine learning pipelines using genetic programming.Read 9 Oct 2026 · epistasislab.github.io

Integrations

The installation documentation lists scikit-learn and offers extra scikit-learn extensions through the tpot[sklearnex] installation option.Read 9 Oct 2026 · epistasislab.github.io

Support

The project directs users to its GitHub issues to report bugs or suggest enhancements and to discuss extensions.Read 9 Oct 2026 · epistasislab.github.io

License

TPOT is free software distributed under the GNU Lesser General Public License version 3 or later, without warranty.Read 9 Oct 2026 · epistasislab.github.io

Founded

2016Read 28 Sep 2026 · epistasislab.github.io

Data handling limit

TPOT does not check whether input data is correctly formatted and assumes the chosen operators can handle the supplied data.Read 9 Oct 2026 · epistasislab.github.io

Features

The current package includes genetic feature selection, flexible search space definitions, multi-objective optimization, and a modular evolutionary algorithm framework.Read 9 Oct 2026 · epistasislab.github.io

Installation

TPOT requires Python and can be installed in a conda environment or manually; the documented Python range is >=3.10 and <3.14.Read 9 Oct 2026 · epistasislab.github.io

Parallel processing

TPOT uses Dask for parallel processing and recommends guarding script code with an if __name__ == "__main__" block.Read 9 Oct 2026 · epistasislab.github.io

Pipeline types

The documentation includes classifiers and regressors, as well as graph, sequential, tree, and union pipeline types.Read 9 Oct 2026 · epistasislab.github.io

Platform caveat

The documentation warns that scikit-learn extensions may have compatibility or performance issues on Arm-based CPUs such as M1 Macs.Read 9 Oct 2026 · epistasislab.github.io

Preprocessing

With preprocessing enabled, TPOT imputes missing values, one-hot encodes categorical features, and standardizes data.Read 9 Oct 2026 · epistasislab.github.io

Preprocessing limit

The documentation says preprocessing is currently fitted and transformed on the entire training set before cross-validation splitting.Read 9 Oct 2026 · epistasislab.github.io

Research focus

The project says TPOT was developed in the Artificial Intelligence Innovation Lab at Cedars-Sinai with NIH funding.Read 9 Oct 2026 · epistasislab.github.io

Plans and prices

Every TPOT plan and price →

Where Specifiction places it

• AutoML Software#18 of 307.3
• Predictive Analytics Software#23 of 377.3