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Found 160 packages
MathNet.Numerics✓
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, .NET Standard 2.0 and .NET Framework 4.6.1 or higher, on Windows, Linux and Mac.
v5.0.0
↙ 58.4M / total
mathnumericstatisticsprobabilityintegration
MathNet.Numerics.Signed✓
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, .NET Standard 2.0 and .NET Framework 4.6.1 or higher, on Windows, Linux and Mac. This package contains strong-named assemblies for legacy use cases (not recommended).
v5.0.0
↙ 36.9M / total
mathnumericstatisticsprobabilityintegration
Accord.Statistics
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 Squares, Discriminant Analysis, Kernel methods and functions and many other related techniques. Provides methods for computing variances, standard deviations, averages, and many other statistical measures. This package is part of the Accord.NET Framework.
v3.8.0
↙ 7.2M / total
accord.netaforge.netframeworkstatisticskernel
Accord.Math
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 for scientific applications. This package is part of the Accord.NET Framework.
v3.8.0
↙ 8.6M / total
accord.netaforge.netframeworkmathdecompositions
Regression
The library for working with regression analysis from Alfapascal
v1.0.5
↙ 1.2K / total
RegressionLinearSplineAlphaPascal
MathNet.Numerics.FSharp✓
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 5.0 or higher, .NET Standard 2.0 and .NET Framework 4.6.1 or higher, on Windows, Linux and Mac.
v5.0.0
↙ 4.0M / total
fsharpF#mathnumericstatistics
pkg
SharpLearning.DecisionTrees
Provides learning algorithms and models for DecisionTree regression and classification.
v0.31.8
↙ 506.5K / total
decisiontreesmachinelearningclassificationregressionmachine
pkg
VisualRegressionTracker
Open source, self hosted solution for visual testing and managing results of visual testing.
v4.9.0
↙ 134.8K / total
pkg
SharpLearning.RandomForest
Provides learning algorithms and models for RandomForest and ExtraTrees regression and classification.
v0.31.8
↙ 373.0K / total
randomforestextratreesmachinelearningclassificationregression
pkg
SharpLearning.Metrics
Provides classification, regression, impurity and ranking metrics.
v0.31.8
↙ 208.5K / total
metricsmachinelearningclassificationregressionmachine
CenterSpace.NMath.Standard.Windows.X64
Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires Visual Studio 2015-2019 C++ x64 runtime. Requires x64 hardware.
v7.4.2.16
↙ 953.9K / total
mathstatisticsnumericsprobabilitylinear
Extreme.Numerics
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 functionality. For optimal performance, we strongly recommend also referencing one of the native packages based on Intel's Math Kernel Library (MKL). Supports .NET 5.0-8.0+, .NET Framework 4.62+, .NET Standard 2.0, and .NET Core 3.1 on Windows, Linux and Mac.
v8.1.25
↙ 1.5M / total
mathstatisticsprobabilitymachinelearning
CsCheck
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: - Automatic shrinking. Gen classes are composable with no need for Arb classes. So less boilerplate. - Random testing and shrinking are parallelized. This and PCG make it very fast. - Shrunk cases have a seed value. Simpler examples can easily be reproduced. - Shrinking can be continued later to give simpler cases for high dimensional problems. - Parallel testing and random shrinking work well together. CsCheck also makes parallel, performance and regression testing simple and fast.
v4.6.1
↙ 314.8K / total
quickcheckrandommodel-basedmetamorphicparallel
pkg
SharpLearning.GradientBoost
Provides learning algorithms and models for GradientBoost regression and classification.
v0.31.8
↙ 140.4K / total
gradientboostmachinelearningclassificationregressionmachine
ImageDiff
A library for producing diffs of images with highlighting.
v1.0.1
↙ 177.1K / total
imagediffdifferencevisualregression
pkg
SharpLearning.Ensemble
Provides ensemble learning for regression and classification.
v0.31.8
↙ 114.0K / total
ensemblelearningmachinelearningclassificationregressionmachine
pkg
SPMeta2.Regression.Core
SPMeta2 common regression package. Proivides core services for regression tests.
v1.0.274.1641
↙ 21.0K / total
SharePointSP2013SP2010O365Office365
pkg
SharpLearning.AdaBoost
Provides learning algorithms and models for AdaBoost regression and classification.
v0.31.8
↙ 104.0K / total
adaboostmachinelearningclassificationregressionmachine
pkg
SPMeta2.Regression.SSOM
SPMeta2 SSOM regression package. Proivides SSOM support for regression tests.
v1.0.274.1641
↙ 16.6K / total
SharePointSP2013SP2010O365Office365
pkg
SharpLearning.Neural
Provides learning algorithms and models for neural net regression and classification.
v0.31.8
↙ 137.4K / total
neuralnetworkconvolutionaldeeplearning
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