Showing 493 open source projects for "java machine learning library"

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  • 1
    This is an attempt to create simple image recognition program in java. Demo here: http://www.youtube.com/watch?v=N4m4j4D3pJU
    Downloads: 0 This Week
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  • 2
    A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
    Downloads: 0 This Week
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  • 3
    BCAR is a library for the associative classification, which denotes "Boosting Class Association Rules". BCAR provides a general tool for classification tasks with various types of input data.
    Downloads: 0 This Week
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  • 4
    Overhead Imagery Research Data Set (OIRDS) - an annotated data library & tools to aid in the development of computer vision algorithms
    Downloads: 6 This Week
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  • 5
    Python Machine learning library with multi-core support. Wraps existing ML libraries in order to be able to run and analyse experiments with one front-end API. Currently supports MLP, GA, GP, ESN and RBF algorithms.
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  • 6
    Blunder is an automated tool for analyzing chained exceptions in Java. It's usefull for classify, generate a customized error message and a list for possible solutions.
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  • 7
    Highly reusable and extensible Decision-Tree (Max-Gain) framework comprising of comprehensive input-processing and display functionality. Handles nominal, linear, continuous data. For preliminary description, refer - http://sushain.com/blog/archives/
    Downloads: 0 This Week
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  • 8
    This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in ะก++.
    Downloads: 1 This Week
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  • 9
    A general purpose Finite State Machine written in Java. It is easy to use, powerful, and fast.
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  • 10
    TrimGA is a lightweight genetic algorithm library written in pure Java 6.0 that can be quickly applied to most optimization problems.
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  • 11

    TimeSleuth - Temporal Rule Discovery

    Temporal and Causal Decision Rules

    TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}.
    Downloads: 0 This Week
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  • 12
    ART - Artificial Reasoning Toolkit
    Java library devoted to handle Genetic Algorithms and Classifier Systems. It has been engineered to be used into agent based simulation models and to search bounded optimal solutions in wide solution spaces. It runs on distributed clusters.
    Downloads: 0 This Week
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  • 13
    UnBFuzzy is an API for fuzzy-logic and learning algorithms for fuzzy systems.
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  • 14

    AraRooter

    Find Arabic Root Word

    Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy.
    Downloads: 0 This Week
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  • 15
    lstm network library
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  • 16
    Spec is a voice control based on the libraries of Sphinx-4.
    Downloads: 0 This Week
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  • 17

    Cinefile

    A category-based approach to exploring film data.

    Cinefile is a prototype of a category-based method of database exploration. It allows the user to identify abstract categories of films by providing examples of category members, learns to classify films as belonging or not belonging to those categories, and provides a graphical interface for exploring and comparing categories. Cinefile is designed to work with data retrieved from the Internet Movie Database (imdb.com). This data is used for classification and is the subject of the...
    Downloads: 0 This Week
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  • 18

    Supertagger

    Software for assigning supertags.

    Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.
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