Showing 5 open source projects for "cost sensitive"

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  • 1
    Light-4J

    Light-4J

    A fast, lightweight and more productive microservices framework

    Light means lightweight, lightning-fast and shedding light on how to program with modern Java SE for cloud-native deployment. I had been working on the Java EE platforms since early 2000 and suffered performance and productivity issues. In 2014, I realized that the IT industry was moving from Monolithic to Microservices and from on-premise data centers to the public clouds. To reduce the production cost for my applications, I need to find a lightweight platform that has a small memory footprint...
    Downloads: 2 This Week
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  • 2
    faasd

    faasd

    A lightweight & portable faas engine

    ... use-cases. To distribute applications to a customer or client. You have a cost sensitive project - run faasd on a 1GB VM for 5-10 USD / mo or on your Raspberry Pi. When you just need a few functions or microservices, without the cost of a cluster.
    Downloads: 0 This Week
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  • 3

    MUMAL2

    Multivariate analysis of MS/MS data using ML techniques

    Program described in the paper: MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm, 2016. By Fabio R. Cerqueira; Adilson M. Ricardo; Alcione P. Oliveira; Armin Graber; Christian Baumgartner.
    Downloads: 0 This Week
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  • 4

    Cost-sensitive Classifiers

    Adaboost extensions for cost-sentive classification

    Adaboost extensions for cost-sentive classification CSExtension 1 CSExtension 2 CSExtension 3 CSExtension 4 CSExtension 5 AdaCost Boost CostBoost Uboost CostUBoost AdaBoostM1 Implementation of all the listed algorithms of the cluster "cost-sensitive classification". They are the meta algorithms which requires base algorithms e.g. Decision Tree Moreover, Voting criteria is also required e.g. Minimum expected cost criteria Input also requires to load an arff file...
    Downloads: 0 This Week
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  • 5

    EGNLA

    Heterogeneous cluster for acceleration of linear algebra computations

    This project deals with a new concept of the heterogeneous grid for acceleration of the numerical linear algebra computing. We design this grid with respect to maximal ratio between cost and computational power. It allows a parallelization of scientific codes with minimal programming effort. We also optimize grid concept to be less sensitive to network parameters.
    Downloads: 0 This Week
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