modAL VS GPflowOpt

Compare modAL vs GPflowOpt and see what are their differences.

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modAL GPflowOpt
4 1
2,119 263
1.3% 1.1%
1.9 1.8
about 1 month ago over 3 years ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

modAL

Posts with mentions or reviews of modAL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-12.

GPflowOpt

Posts with mentions or reviews of GPflowOpt. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-05.
  • [D] Choosing best parameters from an optimization
    3 projects | /r/MachineLearning | 5 Jun 2021
    1- Hyperparameter optimization as already suggested by u/sener87 but I think your validation does not have to be change as it tests generalization as far as I understand you right. If you have more parameter/larger search space, you may look into Bayesian optimization for this task as implemented e.g. with tensorflow, torch or numpy frameworks.

What are some alternatives?

When comparing modAL and GPflowOpt you can also consider the following projects:

active_learning - Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training with torch's DDP.

lightly - A python library for self-supervised learning on images.

paramonte - ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.

agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

pretty-print-confusion-matrix - Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

DataProfiler - What's in your data? Extract schema, statistics and entities from datasets

Encord Active - Open source active learning toolkit to find failure modes in your computer vision models, prioritize data to label next, and drive data curation to improve model performance.

DIgging - Decision Intelligence for digging best parameters in target environment.

baybe - A Bayesian Back End for Design of Experiments

pybads - PyBADS: Bayesian Adaptive Direct Search optimization algorithm for model fitting in Python

Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

k-nearest-neighbors-algorithm - k-nearest neighbors algorithm (k-NN)