Novacta.Analytics 2.0.0

The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org. Prefix Reserved
dotnet add package Novacta.Analytics --version 2.0.0
NuGet\Install-Package Novacta.Analytics -Version 2.0.0
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Novacta.Analytics" Version="2.0.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Novacta.Analytics --version 2.0.0
#r "nuget: Novacta.Analytics, 2.0.0"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install Novacta.Analytics as a Cake Addin
#addin nuget:?package=Novacta.Analytics&version=2.0.0

// Install Novacta.Analytics as a Cake Tool
#tool nuget:?package=Novacta.Analytics&version=2.0.0

Novacta.Analytics

The Novacta.Analytics library provides functionality for data analysis.

The project targets .NET 6, and supports the x86-64 architecture on Windows, Linux, and macOS platforms.

Installation can be performed via NuGet.

Features

Matrix algebra operations

Matrix data presentation and interaction in application UI

Summary statistics

Multivariate data analysis

  • Represent multi-dimensional, weighted points by taking their coordinates with respect to whatever basis using cloud instances.
  • Project clouds along their principal directions by identifying new, uncorrelated variables whose variances enhance our comprehension of the overall cloud variability, possibly approximating the cloud in a lower dimensional space.
  • Compute the principal components of a matrix, an application of principal projections to the classical context in which matrix rows are interpreted as point coordinates taken with respect to bases depending on specific coefficients assigned to the observed variables.
  • Correspondence analysis of a contingency table.
  • Cluster Analysis
    • Discover optimal clusters in a data set by minimizing the sum of intra-cluster squared deviations.
    • Explain existing clusters selecting features by minimizing the Davies-Bouldin index.

Categorical data sets

Randomization

Optimization

Rare event simulation

Documentation

The current documentation includes the following topics.

Versioning

We use SemVer for versioning. For available versions, see the tags on this repository.

Copyrights and Licenses

All source code is Copyright (c) 2018 Giovanni Lafratta.

Novacta.Analytics is licensed under the MIT License.

This project relies on native dynamic-link libraries obtained via the Intel® oneAPI Math Kernel Library customDLL builder. oneAPI MKL is Copyright (c) 2021 Intel® Corporation and licensed under the ISSL terms.

Product Compatible and additional computed target framework versions.
.NET net6.0 is compatible.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
2.0.0 653 2/12/2022
1.0.0 887 4/14/2020

* Added types to operate with matrices of complex values.
* Added matrix singular value decompositions and spectral decompositions of symmetric/Hermitian matrices.
* (Breaking) Indexers that try to avoid dense allocations have been deprecated.
* (Breaking) The 32-bit generation of the x86 architecture is no longer supported.