107 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.

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

A library for producing diffs of images with highlighting.

Numerics.NET (formerly 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... More information

Provides classification, regression, impurity and ranking metrics.

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

Provides learning algorithms and models for GradientBoost regression and classification.

Provides ensemble learning for regression and classification.

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

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.

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

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

Provides learning algorithms and models for XGBoost regression and classification.