Industrial Data Science
in C# and .NET:
Simple. Fast. Reliable.

ILNumerics - Technical Computing

Modern High Performance Tools for Technical

Computing and Visualization in Industry and Science


Machine Learning Toolbox for .NET (C# and Visual Basic)

A number of machine learning algorithms are provided. Every algorithm is optimized for both: memory consumption and execution speed. The range of algorithms spreads from supervised to unsupervised algorithms and each provides a convenient variable parameter list.


Method name Short description
Machine Learning Functions
em Expectation Maximization - estimate centers and covariance of n multivariate normal distributions according to the samples
kmeansclust k Means Clustering - splits the data into a given number of clusters


k Nearest Neighbors - searches k nearest neighbors for every input sample, handles several distances
krr Kernel Ridge Regression - kernelized version of ridge regression, creates and applies the model with a number of different kernels
pca Principal Component Analysis - finds orthogonal directions used to reduce the dimensionality of the data
ridge_regression Ridge Regression - fits a polynomial model to input data