Showing 29 open source projects for "genetic algorithm java"

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  • 1
    PyGAD

    PyGAD

    Source code of PyGAD, Python 3 library for building genetic algorithms

    PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function.
    Downloads: 2 This Week
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  • 2
    Smile

    Smile

    Statistical machine intelligence and learning engine

    Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM...
    Downloads: 4 This Week
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  • 3
    Alink

    Alink

    Alink is the Machine Learning algorithm platform based on Flink

    Alink is Alibaba’s scalable machine learning algorithm platform built on Apache Flink, designed for batch and stream data processing. It provides a wide variety of ready-to-use ML algorithms for tasks like classification, regression, clustering, recommendation, and more. Written in Java and Scala, Alink is suitable for enterprise-grade big data applications where performance and scalability are crucial.
    Downloads: 1 This Week
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  • 4
    Easy Machine Learning

    Easy Machine Learning

    Easy Machine Learning is a general-purpose dataflow-based system

    Machine learning algorithms have become the key components in many big data applications. However, the full potential of machine learning is still far from being realized because using machine learning algorithms is hard, especially on distributed platforms such as Hadoop and Spark. The key barriers come from not only the implementation of the algorithms themselves but also the processing for applying them to real applications which often involve multiple steps and different algorithms. Our...
    Downloads: 0 This Week
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  • ACI Learning: Internal Audit, Cybersecurity, and IT Training Icon
    ACI Learning: Internal Audit, Cybersecurity, and IT Training

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  • 5

    DGRLVQ

    Dynamic Generalized Relevance Learning Vector Quantization

    Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different...
    Downloads: 0 This Week
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  • 6
    Genetic Oversampling Weka Plugin

    Genetic Oversampling Weka Plugin

    A Weka Plugin that uses a Genetic Algorithm for Data Oversampling

    Weka genetic algorithm filter plugin to generate synthetic instances. This Weka Plugin implementation uses a Genetic Algorithm to create new synthetic instances to solve the imbalanced dataset problem. See my master thesis available for download, for further details.
    Downloads: 0 This Week
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  • 7
    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.
    Downloads: 0 This Week
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  • 8
    Machine-Learning-Flappy-Bird

    Machine-Learning-Flappy-Bird

    Machine Learning for Flappy Bird using Neural Network

    ...The neural network receives input features representing the bird’s position relative to the next obstacle and determines whether the bird should flap or remain idle. Over successive generations, a genetic algorithm evolves the neural networks by selecting high-performing agents and recombining their parameters to produce improved offspring. This process allows the AI agents to gradually learn better strategies for navigating the obstacles and surviving longer in the game environment.
    Downloads: 0 This Week
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  • 9

    OWL Machine Learning

    Machine learning algorithm using OWL

    Feature construction and selection are two key factors in the field of Machine Learning (ML). Usually, these are very time-consuming and complex tasks because the features have to be manually crafted. The features are aggregated, combined or split to create features from raw data. This project makes use of ontologies to automatically generate features for the ML algorithms. The features are generated by combining the concepts and relationships that are already in the knowledge base,...
    Downloads: 0 This Week
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  • Apify is a full-stack web scraping and automation platform helping anyone get value from the web. Icon
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  • 10
    Swift AI

    Swift AI

    The Swift machine learning library

    Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the...
    Downloads: 0 This Week
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  • 11

    GA-EoC

    GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations

    ...To enhance classification performances, we propose an ensemble of classifiers that combine the classification outputs of base classifiers using the simplest and largely used majority voting approach. Instead of creating the ensemble using all base classifiers, we have implemented a genetic algorithm (GA) to search for the best combination from heterogeneous base classifiers. The classification performances achieved by the proposed method method on the chosen datasets are promising.
    Downloads: 0 This Week
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  • 12

    DE-HEoC

    DE-based Weight Optimisation for Heterogeneous Ensemble

    We propose the use of Differential Evolution algorithm for the weight adjustment of base classifiers used in weighted voting heterogeneous ensemble of classifier. Average Matthews Correlation Coefficient (MCC) score, calculated over 10-fold cross-validation, has been used as the measure of quality of an ensemble. DE/rand/1/bin algorithm has been utilised to maximize the average MCC score calculated using 10-fold cross-validation on training dataset. The voting weights of base classifiers are...
    Downloads: 0 This Week
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  • 13

    JAABA

    The Janelia Automated Animal Behavior Annotator

    The Janelia Automatic Animal Behavior Annotator (JAABA) is a machine learning-based system that enables researchers to automatically compute interpretable, quantitative statistics describing video of behaving animals. Through our system, users encode their intuition about the structure of behavior by labeling the behavior of the animal, e.g. walking, grooming, or following, in a small set of video frames. JAABA uses machine learning techniques to convert these manual labels into behavior...
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    Downloads: 3 This Week
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  • 14

    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).
    Downloads: 0 This Week
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  • 15
    MODLEM

    MODLEM

    rule-based, WEKA compatible, Machine Learning algorithm

    This project is a WEKA (Waikato Environment for Knowledge Analysis) compatible implementation of MODLEM - a Machine Learning algorithm which induces minimum set of rules. These rules can be adopted as a classifier (in terms of ML). It is a sequential covering algorithm, which was invented to cope with numeric data without discretization. Actually the nominal and numeric attributes are treated in the same way: attribute's space is being searched to find the best rule condition during rule...
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    Downloads: 20 This Week
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  • 16
    Intelligent Keyword Miner

    Intelligent Keyword Miner

    Intelligent SEO keyword miner and predicing tool

    THIS IS A NETBEANS 8.02 PROJECT ENGLISH ONLY This program was made to help me with the patent research. It simply generates the search keywords, based on your upvotes or a downvotes of the input parameters. It can accept a text or URL (text takes a prescedence over the URL). If you input URL, it goes to a page, and learns its text from HTML format. This program is intelligent as it predicts what you may want to search next, based on your personal trends. After searching the...
    Downloads: 0 This Week
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  • 17

    A2y

    Automated Algorithm Synthesis

    Downloads: 0 This Week
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  • 18
    Java application for training and deploying text processing applications such as part-of-speech taggers, based on a re-implementation of Brill's algorithm in Java.
    Downloads: 0 This Week
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  • 19

    Reactor Breeder

    A Genetic Algorithm for Reactors in StarMade

    This software uses a genetic algorithm to "evolve" reactor designs for Schema's space-simulation game, Star-Made (http://star-made.org/). One of the more unique aspects of the game is that ship power management is not as simple as filling a cube with power generation blocks. This mechanism leads to difficulties in getting maximal power generation out of such reactors.
    Downloads: 0 This Week
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  • 20
    EpochX
    EpochX is an open source genetic programming framework, specifically for analysing the properties of evolutionary automatic programming. It supports 3 popular representations - Strongly-Typed GP, Context-Free Grammar GP and Grammatical Evolution.
    Downloads: 0 This Week
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  • 21
    BIL++
    BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
    Downloads: 0 This Week
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  • 22
    BorderFlow
    BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.
    Downloads: 0 This Week
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  • 23
    Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
    Downloads: 0 This Week
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  • 24
    weka outlier is an implementation of outlier detection algorithms for WEKA. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.
    Downloads: 1 This Week
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  • 25
    Maui is a multi-purpose automatic topic indexing algorithm. Given a document, Maui automatically identifies its topics. Depending on the task topics are tags, keywords, keyphrases, vocabulary terms, descriptors or Wikipedia titles.
    Downloads: 0 This Week
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