84 packages returned for Tags:"regression"

Math.NET Numerics is the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Supports .NET 5.0 or higher,... More information

Math.NET Numerics is the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Supports .NET 5.0 or higher,... More information

Contains a matrix extension library, along with a suite of numerical matrix decomposition methods, numerical optimization algorithms for constrained and unconstrained problems, special functions and other tools... More information

F# Modules for Math.NET Numerics, the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Supports .NET... More information

Contains probability distributions, statistical models and methods such as Linear and Logistic regression, Hidden Markov Models, (Hidden) Conditional Random Fields, Principal Component Analysis, Partial Least... More information

Provides learning algorithms and models for DecisionTree regression and classification.

Provides learning algorithms and models for RandomForest and ExtraTrees regression and classification.

Provides classification, regression, impurity and ranking metrics.

A library for producing diffs of images with highlighting.

Provides learning algorithms and models for GradientBoost regression and classification.

Provides ensemble learning for regression and classification.

This is the .Net Standard port of https://github.com/richclement/ImageDiff . Sadly I did not get in contact with him so I'm publishing this.

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general... More information

The Extreme Optimization Numerical Libraries for .NET are a set of libraries for numerical computing and data analysis. This is the main package that contains all the core functionality. For optimal... More information

Provides learning algorithms and models for AdaBoost regression and classification.

The GPU-accelerated version of package CenterSpace.NMath. With a few minor exceptions, such as optional GPU configuration settings, the API is identical between CenterSpace.NMath.Premium and CenterSpace.NMath.... More information

Classes for data manipulation and statistical computation, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of... More information

Provides learning algorithms and models for neural net regression and classification.

CsCheck is a C# random testing library inspired by QuickCheck. It differs in that generation and shrinking are both based on PCG, a fast random number generator. This gives the following advantages: -... More information

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general... More information