Model Selection Python Packages

yellowbrick

Visual analysis and diagnostic tools to facilitate machine learning model selection.

dynesty

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

ultranest

Fit and compare complex models reliably and rapidly. Advanced nested sampling.

sklearndf

DataFrame support for scikit-learn.

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

xrouter-llm

A prompt-aware LLM router that predicts which models can complete each request, then selects the cheapest capable one: 53.2% lower cost and +1.9 pts completion on our tested dataset.

llm-preflight

Local, cross-provider preflight checks for LLM integration changes

evalml

EvalML is an AutoML library written in python.

shap-hypetune

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

hyperactive

A unified interface for optimization algorithms and experiments

greybox

Regression model building and forecasting in R and Python

sklearn-genetic-opt

Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.

gamma-facet

Human-explainable AI.

axiomize-quantum-skills-2-0

Scientific modeling engine (versioned Model IR, dimensional validation, uncertainty) plus quantum-inspired multi-branch reasoning. Python, MCP and REST. MIT.

bayesloop

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

petab-select

Model selection for PEtab

cascade-ml

Small-scale MLOps library

bxa

Bayesian X-ray analysis (nested sampling for Xspec and Sherpa)

llamafit

Find, size, install and verify open-weight LLMs for llama.cpp on your own machine.

compsil

CompSil: Composite Silhouette for Cluster-Count Selection

tpot2

⚠️ DEPRECATED. The work in this repository was merged into the main TPOT project as version 1.0. Please visit the active repository here: https://github.com/EpistasisLab/tpot/tree/main A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

tscv

Time Series Cross-Validation -- an extension for scikit-learn

kulprit

Kullback-Leibler projections for Bayesian model selection in Python

llm-pqr

Provider-neutral LLM model selection using measured quality, latency, cost, capabilities, and hard privacy constraints.