150 projects for "java machine learning library" with 2 filters applied:

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  • 1
    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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  • 2
    Este proyecto constituye una adaptacion y mejora del codigo ANFIS de dominio público de Roger Jang. / This project is an adaptation and improvement of the original public domain ANFIS code of Roger Jang.
    Downloads: 1 This Week
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  • 3
    Artificial neural network with eigenfaces for face recognition
    Downloads: 0 This Week
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  • 4
    GAME stays for Generic Architecture based on Multiple Experts. Its main purpose is to make easy prototyping, test and release of prediction systems. Released by IASC group, university of Cagliari
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  • 5
    GNU FALCO
    Basically the program detects face, extends and saved with the date and time of detection. Thus the operator can identify people from the files located within the PC memory.
    Downloads: 0 This Week
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  • 6
    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.
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  • 7
    Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.
    Downloads: 0 This Week
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  • 8
    Sanchay
    Sanchay is a collection of tools and APIs for language researchers. It has some implementations of NLP algorithms, some flexible APIs, several user friendly annotation interfaces and Sanchay Query Language for language resources.
    Downloads: 0 This Week
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  • 9
    Neuroph OCR - Handwriting Recognition
    Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.
    Downloads: 0 This Week
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  • 10
    A graphical MatLab framework for estimating the parameters of, modeling and simulating static and dynamic linear and polynomial systems in the errors-in-variables context with the intent of comparing various estimation strategies.
    Downloads: 0 This Week
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  • 11
    A java tool for anytime and interactive sequence mining. Aims at providing users with a way of analyzing her activity traces and extract activity schemes from them.
    Downloads: 1 This Week
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  • 12
    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: 0 This Week
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  • 13
    RBM-provisor
    An experimental unsupervised learning method for improvising jazz melodies, based on restricted Boltzmann machines (RBMs) layered into Deep Belief Networks (forms of neural networks).
    Downloads: 0 This Week
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  • 14
    Neural - is neural network engine with object-oriented design. Features: - Supports: backpropogation, RPROP algorithms. - Flexible input/outputs framework. - Distributed calculations.
    Downloads: 0 This Week
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  • 15
    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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  • 16
    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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  • 17
    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.
    Downloads: 0 This Week
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  • 18
    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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  • 19

    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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  • 20
    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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  • 21
    UnBFuzzy is an API for fuzzy-logic and learning algorithms for fuzzy systems.
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  • 22

    AraRooter

    Find Arabic Root Word

    Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy.
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  • 23
    lstm network library
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  • 24

    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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  • 25

    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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