Genetic algorithm library

GA alternatives and similar packages

Based on the "AI" category

• grenade

  9.9 5.0 GA VS grenade

  Practical Deep Learning in Haskell

• hasktorch

  9.8 9.7 GA VS hasktorch

  Torch for tensors and neural networks in Haskell

• opencv

  9.5 6.9 GA VS opencv

  Haskell binding to OpenCV-3.x

• hnn

  9.4 0.0 GA VS hnn

  A reasonably fast and simple neural network library

• nn

  9.3 0.0 GA VS nn

  A tiny neural network

• CV

  8.7 0.0 GA VS CV

  OpenCV based machine vision library

• keera-posture

  8.2 0.0 GA VS keera-posture

  Get notifications when your sitting posture is inappropriate.

• HOpenCV

  8.1 0.0 GA VS HOpenCV

  A binding for the OpenCV computer vision library

• moo

  8.0 3.0 GA VS moo

  Genetic algorithm library

• svm

  7.8 0.0 GA VS svm

  A support vector machine written in Haskell

• genprog

  7.6 0.0 GA VS genprog

  Genetic programming library

• hopfield

  7.5 0.0 GA VS hopfield

  Hopfield Networks, Boltzmann Machines and Clusters

• tensor-safe

  7.4 6.4 GA VS tensor-safe

  Create valid deep neural network architectures

• svm-simple

  6.8 0.0 GA VS svm-simple

  Medium level, simplified, bindings to libsvm

• simple-genetic-algorithm

  6.7 0.0 GA VS simple-genetic-algorithm

  Simple parallel genetic algorithm implementation

• cv-combinators

  6.5 0.0 GA VS cv-combinators

  Functional Combinators for Computer Vision

• neet

  6.5 0.0 GA VS neet

  A NEAT library for Haskell

• simple-neural-networks

  6.2 0.3 GA VS simple-neural-networks

  Simple parallel neural networks implementation

• creatur

  6.0 2.5 GA VS creatur

  Framework for artificial life experiments.

• heukarya

  5.8 0.0 GA VS heukarya

  A genetic programming based on tree structure.

• HSGEP

  5.6 0.0 GA VS HSGEP

  Gene Expression Programming evolutionary algorithm in Haskell

• csp

  5.5 0.0 GA VS csp

  Discrete constraint satisfaction problem (CSP) solver.

• liblinear-enumerator

  5.2 0.0 L1 GA VS liblinear-enumerator

  liblinear iteratee.

• HaVSA

  5.2 0.0 GA VS HaVSA

  An implementation of the Version Space Algebra learning framework.

• SimpleEA

  4.8 0.0 GA VS SimpleEA

  Simple evolutionary algorithm framework.

• neural-network-base

  3.2 0.0 GA VS neural-network-base

  Yet Another High Performance and Extendable Neural Network in Haskell

• hmep

  3.2 1.7 GA VS hmep

  HMEP Multi Expression Programming – a genetic programming variant

• huff

  3.2 0.0 GA VS huff

  A fast-foward-based planner

• CarneadesDSL

  2.9 0.0 GA VS CarneadesDSL

  An implementation and DSL for the Carneades argumentation model.

• fei-nn

  2.2 6.5 GA VS fei-nn

  Train a neural network with MXNet in Haskell.

• nondeterminism

  1.9 0.0 GA VS nondeterminism

  A monad and monad transformer for nondeterministic computations.

• Etage

  1.8 0.0 GA VS Etage

  A general data-flow framework

• attoparsec-arff

  1.8 0.0 GA VS attoparsec-arff

  An ARFF file parser using Attoparsec

• mxnet-nn

  1.8 5.4 GA VS mxnet-nn

  Train a neural network with MXNet in Haskell.

• fei-dataiter

  1.6 3.1 GA VS fei-dataiter

  mxnet dataiters

• simple-genetic-algorithm-mr

  1.3 0.0 GA VS simple-genetic-algorithm-mr

  Simple parallel genetic algorithm implementation

• fei-base

  1.2 6.9 GA VS fei-base

  FFI to MXNet

• fei-cocoapi

  1.2 5.6 GA VS fei-cocoapi

  Cocodataset with cocoapi

• fei-examples

  1.2 6.5 GA VS fei-examples

  fei examples

• mxnet-dataiter

  - - GA VS mxnet-dataiter

  mxnet dataiters

• sandlib

  - - GA VS sandlib

  SAND data serialization and manipulation library

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