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What is ndCurveMaster?

ndCurveMaster is an advanced software solution tailored for fitting curves across multiple variables. It seamlessly applies nonlinear equations to datasets that consist of either observed or measured values. This versatile tool accommodates curve and surface fitting across dimensions ranging from 2D to 5D and beyond. Regardless of the complexity or the number of variables, ndCurveMaster is equipped to process any type of data. For instance, it can effectively determine the ideal equations for a dataset featuring six input variables (x1 through x6) and an output variable Y, exemplified by an equation such as Y = a0 - a1 - exp(x1)0.5 + a2 ln(x2)8... + a6 x65.2, which accurately reflects the measured values. Employing machine learning numerical techniques, ndCurveMaster automatically identifies the most appropriate nonlinear regression function for your dataset, revealing the intricate relationships between inputs and outputs. The software supports a variety of curve fitting methods, encompassing linear, polynomial, and nonlinear approaches. Additionally, it incorporates critical validation and goodness-of-fit assessments to ensure precision. It further enhances its capabilities by providing sophisticated evaluations, including the identification of overfitting and multicollinearity through tools like the Variance Inflation Factor (VIF) and the Pearson correlation matrix, making it an invaluable resource for data analysis. Overall, ndCurveMaster stands out as a robust tool for researchers and analysts seeking to understand complex data relationships.

What is DataMelt?

DataMelt, commonly referred to as "DMelt," is a versatile environment designed for numerical computations, data analysis, data mining, and computational statistics. It facilitates the plotting of functions and datasets in both 2D and 3D, enables statistical testing, and supports various forms of data analysis, numeric computations, and function minimization. Additionally, it is capable of solving linear and differential equations, and provides methods for symbolic, linear, and non-linear regression. The Java API included in DataMelt integrates neural network capabilities alongside various data manipulation techniques utilizing different algorithms. Furthermore, it offers support for symbolic computations through Octave/Matlab programming elements. As a computational environment based on a Java platform, DataMelt is compatible with multiple operating systems and supports various programming languages, distinguishing it from other statistical tools that often restrict users to a single language. This software uniquely combines Java, the most prevalent enterprise language globally, with popular data science scripting languages such as Jython (Python), Groovy, and JRuby, thereby enhancing its versatility and user accessibility. Consequently, DataMelt emerges as an essential tool for researchers and analysts seeking a comprehensive solution for complex data-driven tasks.

Media

Media

Integrations Supported

Pascal
Python

Integrations Supported

Apache NetBeans
Eclipse BIRT

API Availability

API Availability

Has API

Pricing Information

€289
ndCurveMaster WIN/MAC – Web Download
LIFETIME License
Free Trial Offered?

Pricing Information

$0
Access to full documentation (examples, Java API documentation, online manual) requires one-time membership payment (20$/user)
Free Version

Supported Platforms

Windows
Mac

Supported Platforms

Android
Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

SigmaLab Tomas Cepowski

Date Founded

2017

Company Location

Poland

Company Website

www.ndcurvemaster.com

Company Facts

Organization Name

jWork.ORG

Date Founded

2005

Company Location

United States

Company Website

datamelt.org

Categories and Features

Statistical Analysis

Analytics
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Visualization

Categories and Features

Artificial Intelligence

For Healthcare
Image Recognition
Machine Learning
Natural Language Processing
Predictive Analytics

Data Analysis

Data Discovery
Data Visualization
Predictive Analytics
Regression Analysis
Statistical Modeling
Text Analytics

Data Mining

Data Extraction
Data Visualization
Machine Learning
Predictive Modeling
Statistical Analysis
Text Mining

Data Visualization

Analytics
Simulation Models
Visual Discovery

Deep Learning

Convolutional Neural Networks
Document Classification
ML Algorithm Library
Model Training
Self-Learning
Visualization

Education

Not specified

Neural Network

Not specified

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Simulation
Survival Analysis
Time Series
Visualization

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