modAL VS k-nearest-neighbors-algorithm

Compare modAL vs k-nearest-neighbors-algorithm and see what are their differences.

modAL

A modular active learning framework for Python (by modAL-python)
scikit-learn Machine Learning Python active-learning machine-learning-library machine-learning-algorithms machine-learning-api active-learning-module bayesian-optimization
Source Code
modal-python.github.io
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k-nearest-neighbors-algorithm

k-nearest neighbors algorithm (k-NN) (by umairshabbir-83)
knn-algorithm knn-regression Machine Learning machine-learning-algorithms Python
Source Code
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modAL k-nearest-neighbors-algorithm
4 1
2,140 0
1.5% -
1.9 2.4
2 months ago 3 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.

k-nearest-neighbors-algorithm

Posts with mentions or reviews of k-nearest-neighbors-algorithm. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing modAL and k-nearest-neighbors-algorithm 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.

GPflowOpt - Bayesian Optimization using GPflow

paramonte - ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.

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

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

baybe - Bayesian Optimization and Design of Experiments

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.

deep-active-learning - Deep Active Learning

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

modAL vs active_learning modAL vs GPflowOpt modAL vs paramonte modAL vs lightly modAL vs pretty-print-confusion-matrix modAL vs baybe modAL vs DataProfiler modAL vs Encord Active modAL vs DIgging modAL vs deep-active-learning modAL vs pybads