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Description
KEEL (Knowledge Extraction based on Evolutionary Learning) is a Java-based open-source software tool licensed under GPLv3 that facilitates a diverse array of knowledge data discovery tasks. Featuring an intuitive graphical user interface that emphasizes data flow, KEEL enables users to design experiments incorporating various datasets and computational intelligence algorithms, with a particular focus on evolutionary algorithms, to evaluate their effectiveness. The software encompasses an extensive range of traditional knowledge extraction techniques, data preprocessing methods—including training set selection, feature selection, discretization, and imputation for missing values—as well as computational intelligence learning algorithms, hybrid models, and statistical methods for experiment comparison. This comprehensive suite allows researchers to conduct thorough analyses of innovative computational intelligence approaches in relation to established methods. Furthermore, KEEL has been specifically crafted to serve dual purposes: advancing research and enhancing educational outcomes in the field. Its versatility makes it an invaluable resource for both academic and practical applications in knowledge discovery.
Description
The development of large-scale physical quantum computers is proving to be a formidable task, and in parallel with efforts to create these machines, considerable attention is being directed towards crafting effective quantum algorithms. Without a fully realized large quantum computer, it becomes essential to utilize precise software simulations on classical systems to replicate the execution of these quantum algorithms, allowing researchers to analyze quantum computer behavior and refine their designs. In addition to simulating ideal, error-free quantum circuits on a faultless quantum computer, the QX simulator offers the capability to model realistic noisy executions by incorporating various error models, such as depolarizing noise. Users have the option to activate specific error models and set a physical error probability tailored to mimic a particular target quantum computer. This defined error rate can be based on factors like gate fidelity and qubit decoherence characteristics of the intended platform, ultimately aiding in the realistic assessment of quantum computation capabilities. Thus, these simulations not only inform the design of future quantum computers but also enhance our understanding of the complexities involved in quantum processing.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Keel
Website
www.keel.es/
Vendor Details
Company Name
Quantum Computing Simulation
Website
quantum-studio.net
Product Features
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining