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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.
What is JMP Statistical Software?
JMP is a versatile data analysis application that works seamlessly on both Mac and Windows platforms, offering a blend of advanced statistical features and captivating interactive visualizations.
Its intuitive drag-and-drop interface streamlines the data importation and analysis process, complemented by interconnected graphs, a vast array of sophisticated analytic tools, a built-in scripting language, and multiple sharing functionalities, all designed to enhance users' ability to examine their datasets both efficiently and effectively.
Originally developed in the 1980s to capitalize on the advantages of graphical user interfaces in personal computing, JMP has continually progressed by integrating cutting-edge statistical methodologies and tailored analysis techniques from various sectors with each new iteration. Additionally, John Sall, the organization's founder, plays an active role as the Chief Architect, ensuring that the software evolves to meet the dynamic needs of analytical technology. This commitment to innovation and user experience underscores JMP's reputation as a leading choice for data analysis across numerous fields.
Integrations Supported
Amazon Aurora
Amazon Redshift
Azure SQL Database
FACS
Google Sheets
Hive
IBM Db2
JSON
MATLAB
Microsoft Access
Integrations Supported
Amazon Aurora
Amazon Redshift
Azure SQL Database
FACS
Google Sheets
Hive
IBM Db2
JSON
MATLAB
Microsoft Access
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$1320/year/user
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
Keel
Company Website
www.keel.es/
Company Facts
Organization Name
JMP Statistical Discovery
Date Founded
1989
Company Location
United States
Company Website
www.jmp.com
Categories and Features
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Categories and Features
Dashboard
Annotations
Data Source Integrations
Functions / Calculations
Interactive
KPIs
OLAP
Private Dashboards
Public Dashboards
Scorecards
Themes
Visual Analytics
Widgets
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis
Statistical Analysis
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization