HSGEP VS neet

Compare HSGEP vs neet and see what are their differences.

HSGEP

Haskell Gene Expression Programming Library (by mjsottile)
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neet

Neuroevolution of Augmented Topologies (NEAT) -- in Haskell (by raymoo)
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HSGEP neet
- -
10 12
- -
0.0 0.0
about 6 years ago almost 7 years ago
Mathematica Haskell
BSD 3-clause "New" or "Revised" License GNU General Public License v3.0 only
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.

HSGEP

Posts with mentions or reviews of HSGEP. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning HSGEP yet.
Tracking mentions began in Dec 2020.

neet

Posts with mentions or reviews of neet. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning neet yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing HSGEP and neet you can also consider the following projects:

creatur - Framework for artificial life and other evolutionary algorithms.

hnn - haskell neural network library

genprog - Genetic programming library

HaVSA - HaVSA (Have-Saa) is a Haskell implementation of the Version Space Algebra Machine Learning technique described by Tessa Lau.

hopfield - hopfield

HOpenCV - Haskell bindings for OpenCV

tensor-safe - A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.

csp - Constraint satisfaction problem (CSP) solvers for Haskell

grenade - Deep Learning in Haskell

svm-simple - Simplified interface to bindings-svm

moo - Genetic algorithm library for Haskell. Binary and continuous (real-coded) GAs. Binary GAs: binary and Gray encoding; point mutation; one-point, two-point, and uniform crossover. Continuous GAs: Gaussian mutation; BLX-α, UNDX, and SBX crossover. Selection operators: roulette, tournament, and stochastic universal sampling (SUS); with optional niching, ranking, and scaling. Replacement strategies: generational with elitism and steady state. Constrained optimization: random constrained initialization, death penalty, constrained selection without a penalty function. Multi-objective optimization: NSGA-II and constrained NSGA-II.

CV - Haskell wrappers and utilities for OpenCV machine vision library

HSGEP vs creatur neet vs hnn HSGEP vs genprog neet vs HaVSA HSGEP vs hopfield neet vs HOpenCV HSGEP vs tensor-safe neet vs csp HSGEP vs grenade neet vs svm-simple HSGEP vs moo neet vs CV