Showing 5 open source projects for "random"

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  • Our Free Plans just got better! | Auth0 Icon
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  • Deliver trusted data with dbt Icon
    Deliver trusted data with dbt

    dbt Labs empowers data teams to build reliable, governed data pipelines—accelerating analytics and AI initiatives with speed and confidence.

    Data teams use dbt to codify business logic and make it accessible to the entire organization—for use in reporting, ML modeling, and operational workflows.
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  • 1
    Apache HBase

    Apache HBase

    Get random, realtime read/write access to your Big Data

    Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables, billions of rows X millions of columns, atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. A Distributed Storage System for Structured Data by Chang et al.
    Downloads: 8 This Week
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  • 2
    apache spark data pipeline osDQ

    apache spark data pipeline osDQ

    osDQ dedicated to create apache spark based data pipeline using JSON

    This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to...
    Downloads: 1 This Week
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  • 3

    Random Bits Forest

    RBF: a Strong Classifier/Regressor for Big Data

    We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions.
    Downloads: 0 This Week
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  • 4

    Random Bits Regression

    Random Bits Regression is a strong general predictor.

    We proposed an accurate, robust and fast general predictor (RBR) for regression and classification in big data era. The application of this method is very broad, from science to industry, finance and health. The accuracy and robustness improvement of our method over existing method could bring huge benefits in some critical applications. For example, natural disaster prediction, stock price prediction, personal/population disease prediction. The fast-speed nature of our method not only...
    Downloads: 0 This Week
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  • Dun and Bradstreet Connect simplifies the complex burden of data management Icon
    Dun and Bradstreet Connect simplifies the complex burden of data management

    Our self-service data management platform enables your organization to gain a complete and accurate view of your accounts and contacts.

    The amount, speed, and types of data created in today’s world can be overwhelming. With D&B Connect, you can instantly benchmark, enrich, and monitor your data against the Dun & Bradstreet Data Cloud to help ensure your systems of record have trusted data to fuel growth.
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  • 5

    Red-RF

    Reduced Random Forest for big data

    ...Dalkilic. Red-RF: Reduced Random Forests using priority voting & dynamic data reduction. In IEEE BigData Congress'2015. H. Mohsen, H. Kurban, M. Jenne and M. Dalkilic (2014). A New Set of Random Forests with Varying Dynamic Data Reduction and Voting Techniques. In IEEE DSAA'2014. Code, README file, and a sample input file are available in Files/ directory above.
    Downloads: 0 This Week
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