Showing 14 open source projects for "flat file databases"

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  • 1
    dibnn

    dibnn

    Drop In the Bucket Neural Networks

    One more lightweight neural network in C.
    Downloads: 0 This Week
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  • 2
    OpenNN - Open Neural Networks Library

    OpenNN - Open Neural Networks Library

    Machine learning algorithms for advanced analytics

    OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. Some typical applications of OpenNN are business intelligence (customer segmentation, churn prevention…), health care (early diagnosis, microarray analysis…) and engineering (performance optimization, predictive maitenance…). OpenNN does not deal with computer vision or natural language processing. The main advantage of OpenNN is its...
    Downloads: 11 This Week
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  • 3

    entity-metadata

    Lists of people, churches, and other entities

    Here are lists of entities, such as people, businesses, and churches. These are large files related to this repository https://github.com/az0/entity-metadata
    Downloads: 0 This Week
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  • 4
    The goal of this project is to investigate optimal ways to do genre classification for the ten indigenous South African languages. Funded by Dept of Arts and Culture of the SA Government. http://www.trifonius.co.za/projects/genre-classification
    Downloads: 0 This Week
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  • 5
    ChoiceMaker
    Record matching software
    Downloads: 0 This Week
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  • 6
    Adaptive Gaussian Filtering

    Adaptive Gaussian Filtering

    Machine learning with Gaussian kernels.

    Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation...
    Downloads: 1 This Week
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  • 7
    LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings.
    Downloads: 0 This Week
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  • 8
    DocCO

    DocCO

    Non-disjoint groupping of Documents based on word sequence approach

    This is a GUI for learning non disjoint groups of documents based on Weka machine learning framework. It offers the possibility to make non disjoint clustering of documents using both vectorial and sequential representation (word sequence approach based on WSK kernel). All data format supported by WEKA could be used in DocCO. Data could be loaded from files, from databases or from specified URL. All the preprocessing techniques implemented in WEKA could be used before performing the learning.
    Downloads: 0 This Week
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  • 9
    yacaree
    yacaree: Yet Another Closure-based Association Rules Experimentation Environment (Development stalled here, check out under Wiki to find where it went.)
    Downloads: 0 This Week
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  • 10
    Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation
    Downloads: 0 This Week
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  • 11
    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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  • 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
    Multiclass machine learning
    Downloads: 0 This Week
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  • 14
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
    Downloads: 0 This Week
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