Showing 4 open source projects for "optimization"

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    LakshmiDROP

    LakshmiDROP

    Fixed Income Analytics, Portfolio Construction, Asset Backed Cost

    DROP implements the model libraries and provides systems for fixed income valuation and adjustments, asset allocation and transaction cost analytics, and supporting libraries in numerical optimization and statistical learning. DROP is composed of four main libraries: [Asset Allocation] (https://lakshmidrip.github.io/DROP/AssetAllocationModule.html) [Fixed Income Analytics] (https://lakshmidrip.github.io/DROP/FixedIncomeModule.html) [Numerical Optimization] (https://lakshmidrip.github.io/DROP/NumericalOptimizerModule.html) [Statistical Learning] (https://lakshmidrip.github.io/DROP/StatisticalLearningModule.html)
    Downloads: 0 This Week
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  • 2
    Neural Libs

    Neural Libs

    Neural network library for developers

    ...The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.
    Downloads: 0 This Week
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  • 3

    AlgART Java Libraries

    Open source library for processing arrays and matrices

    ...Main features: 63-bit addressing of array elements (64-bit long int indexes), memory model concept (allowing storing data in different schemes from RAM to mapped disk files), wide usage of lazy evaluations, built-in multithreading optimization for multi-core processors, wide set of image processing algorithms over matrices, etc. - please see at the site. Almost all classes and methods are thoroughly documented via JavaDoc (you may read full JavaDoc at the site).
    Downloads: 0 This Week
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  • 4
    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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