Showing 4 open source projects for "data mining algorithm php"

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  • 1
    DocWire SDK

    DocWire SDK

    Award-winning modern data processing SDK in C++20

    DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to...
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  • 2
    AES Everywhere

    AES Everywhere

    Cross Language AES 256 Encryption Library

    AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt.
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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. In conclusion, RBF is a novel framework that performs strongly especially on data...
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  • 4
    Zebra_MPTT

    Zebra_MPTT

    A PHP implementation of the modified preorder tree traversal algorithm

    Zebra_MPTT is a PHP class that provides an implementation of the modified preorder tree traversal algorithm making it easy for you to use MPTT in your PHP applications. It provides methods for adding nodes anywhere in the tree, deleting nodes, moving and copying nodes around the tree and methods for retrieving various information about the nodes.
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