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Description
Automated variable selection helps to pinpoint essential variables along with their interactions, while effective visualization techniques enhance understanding of data and model behaviors. Additionally, the execution of batch commands complements SQL queries and dataset exploration. Pre-processing and post-processing steps are crucial for variable creation and output constraints, among other tasks. Models can be readily deployed through ActiveX (i.e., OCX) controls or DLLs, making implementation straightforward. The suite of advanced modeling algorithms encompasses regression, neural networks, self-organizing maps, dynamic clustering, decision trees, fuzzy logic, and genetic algorithms. Predictive Dynamix offers robust computational intelligence software that serves a wide array of applications, including forecasting, predictive modeling, pattern recognition, classification, and optimization, catering to various industries. Leveraging modern neural network technologies, these solutions provide powerful mechanisms for tackling complex challenges in forecasting and pattern recognition. Multi-layer perceptron neural networks are particularly noteworthy for their architecture, enabling multiple coefficients for each input variable, thus enhancing the model's adaptability and accuracy. This versatility in neural network design is crucial for addressing the diverse needs of contemporary data analysis challenges.
Description
WizWhy analyzes how the values of one data field are influenced by the values of other fields in the dataset. The analysis hinges on a dependent variable chosen by the user, while the remaining fields act as independent variables or conditions. This dependent variable can be examined in two ways: as a Boolean value or as a continuous measurement.
Users have the ability to refine their analysis by setting various parameters, including the minimum probability for rule formation, the least number of instances required for each rule, and the comparative costs associated with false negatives versus false positives.
WizWhy identifies and presents a series of rules that connect the dependent variable with other fields, expressing these rules using if-then and if-and-only-if constructs. Based on the identified rules, WizWhy highlights significant patterns, reveals unexpected rules that may indicate interesting phenomena, and points out unusual cases within the dataset. Additionally, WizWhy is capable of making predictions for new instances by leveraging the established rules.
API Access
Has API
API Access
Has API
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Integrations
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Integrations
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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
Predictive Dynamix
Founded
1999
Website
predictivedynamix.com/dmsuite.htm
Vendor Details
Company Name
WizSoft
Founded
1983
Country
United States
Website
www.wizsoft.com/products/wizwhy/
Product Features
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
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
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
