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What is SHARK?

SHARK is a powerful and adaptable open-source library crafted in C++ for machine learning applications, featuring a comprehensive range of techniques such as linear and nonlinear optimization, kernel methods, and neural networks. This library is not only a significant asset for practical implementations but also for academic research projects. Built using Boost and CMake, SHARK is cross-platform and compatible with various operating systems, including Windows, Solaris, MacOS X, and Linux. It operates under the permissive GNU Lesser General Public License, ensuring widespread usage and distribution. SHARK strikes an impressive balance between flexibility, ease of use, and high computational efficiency, incorporating numerous algorithms from different domains of machine learning and computational intelligence, which simplifies integration and customization. Additionally, it offers distinctive algorithms that are, as far as we are aware, unmatched by other competing frameworks, enhancing its value as a resource for developers and researchers. As a result, SHARK stands out as an invaluable tool in the ever-evolving landscape of machine learning technologies.

What is Keel?

KEEL, which stands for Knowledge Extraction based on Evolutionary Learning, is an open-source software tool developed in Java and licensed under GPLv3, aimed at supporting a wide range of knowledge data discovery tasks. It features a user-friendly graphical interface that prioritizes data flow, allowing users to create experiments that utilize different datasets and computational intelligence algorithms, particularly those based on evolutionary strategies, to assess their performance. The software offers a broad spectrum of standard knowledge extraction methodologies, as well as data preprocessing techniques—such as training set selection, feature selection, discretization, and imputation for missing values—alongside various computational intelligence learning algorithms, hybrid models, and statistical methods for comparing experimental results. This all-encompassing toolkit enables researchers to perform in-depth analyses of novel computational intelligence strategies against traditional approaches. Moreover, KEEL has been intentionally designed to fulfill two main objectives: to promote research advancement and to improve educational experiences in the domain of knowledge discovery. Its adaptability and functionality make it an essential tool for both scholarly pursuits and real-world applications in the field of knowledge extraction. Ultimately, the ongoing development of KEEL ensures that it remains relevant and effective for its users.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

SHARK

Date Founded

2018

Company Website

image.diku.dk/shark/sphinx_pages/build/html/index.html

Company Facts

Organization Name

Keel

Company Website

www.keel.es/

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

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