Showing 5 open source projects for "strategy java"

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  • 1
    ta4j

    ta4j

    A Java library for technical analysis

    Ta4j is an open-source Java library for technical analysis. It provides the basic components for the creation, evaluation, and execution of trading strategies. Ta4j is available on Maven Central. You can also download example code from the maven central repository. The wiki is the best place to start learning about ta4j. For more detailed questions, please use the issues tracker.
    Downloads: 5 This Week
    Last Update:
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  • 2
    Open Source Data Quality and Profiling

    Open Source Data Quality and Profiling

    World's first open source data quality & data preparation project

    This project is dedicated to open source data quality and data preparation solutions. Data Quality includes profiling, filtering, governance, similarity check, data enrichment alteration, real time alerting, basket analysis, bubble chart Warehouse validation, single customer view etc. defined by Strategy. This tool is developing high performance integrated data management platform which will seamlessly do Data Integration, Data Profiling, Data Quality, Data Preparation, Dummy Data...
    Downloads: 2 This Week
    Last Update:
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  • 3

    UNSW Metadata Stores (ResData)

    An institutional research metadata management repository.

    ResData is an institutional metadata repository to facilitate effective management, discovery and sharing of institutional research data collections. It integrates with institutional enterprise systems, such as HR and Grant management systems to facilitate re-use of existing information, such as People and Project records. ResData has been developed by the Library Repository Services, University of New South Wales. The work was supported by the Australian National Data Service (ANDS)...
    Downloads: 1 This Week
    Last Update:
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  • 4

    AdPreqFr4SL

    Adaptive Prequential Learning Framework

    The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we...
    Downloads: 0 This Week
    Last Update:
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  • 5
    Application of neural network to predict the future of stock exchange, aerospace ( ufo trajectory ), sound, image, noise, scientific or medical data. You need , by example, 100 days of a numeric data and the number of days to predict (by example 7 days).
    Downloads: 0 This Week
    Last Update:
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