Search Results for "genetic programming"
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Showing 111 open source projects for "genetic programming"
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gplearn
Genetic Programming in Python, with a scikit-learn inspired API
gplearn implements Genetic Programming in Python, with a scikit-learn-inspired and compatible API. While Genetic Programming (GP) can be used to perform a very wide variety of tasks, gplearn is purposefully constrained to solving symbolic regression problems. This is motivated by the scikit-learn ethos, of having powerful estimators that are straightforward to implement. -
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Evolutionary.jl
Evolutionary & genetic algorithms for Julia
A Julia package for evolutionary & genetic algorithms. The package can be installed with the Julia package manager. -
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TPOT
A Python Automated Machine Learning tool that optimizes ML
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. -
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GOBU
Gene Browsing Utility
Gene Ontology Browsing Utility (hereinafter, GOBU, pronounced as "go-boo") is a browsing and manipulating tool for Post-Pipeline genetic data, especially useful for data with GO annotations. With help of GOBU, we expect biologists and their cooperating technicians can pay less effort on common programming stuff. At the same time, GOBU provides an Extendable Architecture which guarantees the possibility of 1. Arbitrary Data Description, 2. Data Integration, and 3. ... -
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Venice is a stock market trading programme that supports portfolio management, charting, technical analysis, paper trading and genetic programming. Venice runs in a graphical user interface with online help and has full documentation.
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NKTgLaw
Core library & API for the NKTg Law (Nguyen Khanh Tung). Includes core
Core library & API for the NKTg Law (Nguyen Khanh Tung). Includes core implementation, REST/gRPC API, and 150+ client wrappers -
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irixjoker-sensing-utils
sensing in IRIX emulator lib
Uses machine learning to compute with genetic programming for emulators. -
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Algorithms Math Models
MATLAB implementations of algorithms
...The repository gathers implementations and case studies across many topics commonly used in contest solutions: optimization (linear, integer, goal and nonlinear programming), heuristic and metaheuristic methods (simulated annealing, genetic algorithms, immune algorithms), neural networks and time-series methods, interpolation and regression, graph theory, cellular automata, grey systems, fuzzy models, partial/ordinary differential equations, and multivariate analysis, among others. The codebase is organized into topic folders (e.g., HeuristicAlgorithm, IntegerProgramming, NeuralNetwork, TimeSeries) and includes dozens of worked examples and links to textbook/source materials that the author used to assemble the collection. -
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quire-lang
A programming language for genetic data
quire is a scripting language for performing calculations on information from genetic experiments. Although quire is capable of performing arbitrary calculations, it is really a domain-specific language driven by convenience in working in the problem domain over speed or memory usage. quire has a facility to add in binary modules to perform more intensive calculations. -
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RGP Eugenics
Eugenics assumptions in genetic programing
Development of solutions in an automatic way using genetic programming and evolutionary algorithms is powerful. Assuming random starting point and following evolution principles we are capable to solve very complex problems. Question is what if we know some sub-optimal solutions and the evolution process will get so-called good start? The general purpose of the project is to get purely empirical answers for such question. -
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TurboGP
Genetic Programming library in Python
TurboGP is a Genetic Programming library written entirely in Python, primarily aimed at Machine Learning tasks. Currently being developed, and in beta version. Lino Rodriguez-Coayahuitl et al. 2020 -
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The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. ...
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popt4jlib
Parallel Optimization Library for Java
popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known network flow and other graph algorithms. ... -
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This application allow user to predict dissolution profile of solid dispersion systems based on algorithms like symbolic regression, deep neural networks, random forests or generalized boosted models. Those techniques can be combined to create expert system. Application was created as a part of project K/DSC/004290 subsidy for young researchers from Polish Ministry of Higher Education.
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Chronological Cohesive Units
The experimental source code for the paper
The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming" -
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Genetic Programming Classifier is a distributed evolutionary data classification program. It uses the ensemble method implemented under a parallel co-evolutionary Genetic Programming technique.
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JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included. Legal notice/Impressum: Klaus Meffert An der Struth 25 D-65510 Idstein sourceforge <at> klausmeffert.de
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MOEA Framework
A Free and Open Source Java Framework for Multiobjective Optimization
The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3 and MOEA/D. In addition, the MOEA Framework provides the tools necessary to rapidly design, develop, execute and statistically test optimization algorithms. -
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Virtual Stack Machine
A virtual stack machine for Genetic Programming.
A virtual stack machine for Genetic Programming. This is highly optimized for speed. All edge cases and boundary conditions are effectively trapped and handled. -
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Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.
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Genetic Algorithms Engine - Blackjack
A genetic algortihm engine that evolves blackjack basic strategy.
This project is a genetic algorithm engine able to be reused for other projects with minimal additional programming. The genetic algorithm engine currently plays many blackjack hands for the fitness function and produces a result similar to blackjack basic strategy. To see it in action, download the zip file and run either: GABlackjack_Demo.exe (quick) or GABlackjack_Long.exe (slow, but it achieves better results). -
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Java Beagle
A symbolic regression platform in java
Java beagle is my gratitude for genetic programming. It is based on beagle puppy, by open-beagle project. It is mainly designed for symbolic regression tasks. It implements a number of other algorithms for more efficient symbolic regression. These include lexicographic parsimony pressure, linear scaling and subtree caching. -
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dnarand
dnarand is a highly customizable DNA sequences writer
...Plus, it's possible to tell dnarand which is our favorite GC ratio, so that it can simulate AT-rich or GC-rich genomes, and choose our favorite genetic code from all available Ncbi's ones. I'm actively adding new features.
