Accord.MachineLearning 3.3.1-alpha

Contains Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework.

Showing the top 20 packages that depend on Accord.MachineLearning.

Packages Downloads
QuantConnect.Algorithm.CSharp
QuantConnect LEAN Engine: Algorithm.CSharp Project - A collection of C# algorithm demonstrations for how to use the API
46
QuantConnect.Algorithm.CSharp
QuantConnect LEAN Engine: Algorithm.CSharp Project - A collection of C# algorithm demonstrations for how to use the API
45
QuantConnect.Algorithm.CSharp
QuantConnect LEAN Engine: Algorithm.CSharp Project - A collection of C# algorithm demonstrations for how to use the API
44
QuantConnect.Algorithm.CSharp
QuantConnect LEAN Engine: Algorithm.CSharp Project - A collection of C# algorithm demonstrations for how to use the API
43
QuantConnect.Algorithm.CSharp
Lean Engine is an open-source, platform agnostic C# and Python algorithmic trading engine. Allows strategy research, backtesting and live trading with Equities, FX, CFD, Crypto, Options and Futures Markets.
42
QuantConnect.Algorithm.CSharp
QuantConnect LEAN Engine: Algorithm.CSharp Project - A collection of C# algorithm demonstrations for how to use the API
42
QuantConnect.Algorithm.CSharp
QuantConnect LEAN Engine: Algorithm.CSharp Project - A collection of C# algorithm demonstrations for how to use the API
41
QuantConnect.Algorithm.CSharp
QuantConnect LEAN Engine: Algorithm.CSharp Project - A collection of C# algorithm demonstrations for how to use the API
40
QuantConnect.Algorithm.CSharp
Lean Engine is an open-source, platform agnostic C# and Python algorithmic trading engine. Allows strategy research, backtesting and live trading with Equities, FX, CFD, Crypto, Options and Futures Markets.
40

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3.8.2-alpha 41 04/13/2026
3.8.1-alpha 31 04/13/2026
3.8.0 36 04/13/2026
3.7.3-alpha 35 04/13/2026
3.7.2-alpha 35 04/13/2026
3.7.1-alpha 37 04/13/2026
3.7.0 43 04/13/2026
3.6.4-alpha 30 04/13/2026
3.6.3-alpha 30 04/13/2026
3.6.2-alpha 32 04/13/2026
3.6.1-alpha 33 04/13/2026
3.6.0 34 04/13/2026
3.5.4-alpha 34 04/13/2026
3.5.3-alpha 32 04/13/2026
3.5.2-alpha 35 04/13/2026
3.5.1-alpha 33 04/13/2026
3.5.0 32 04/13/2026
3.4.2-alpha 34 04/13/2026
3.4.1-alpha 34 04/13/2026
3.4.0 31 04/13/2026
3.3.2-alpha 35 04/13/2026
3.3.1-alpha 32 04/13/2026
3.3.0 32 04/13/2026
3.2.3-alpha 31 04/13/2026
3.2.2-alpha 33 04/13/2026
3.2.1-alpha 35 04/13/2026
3.2.0 30 04/13/2026
3.1.0-alpha 39 04/13/2026
3.0.2 33 04/13/2026
3.0.1-alpha 39 04/13/2026
3.0.0-alpha 28 04/13/2026
2.15.0 39 04/13/2026
2.14.6-alpha 38 04/13/2026
2.14.5-alpha 35 04/13/2026
2.14.4-alpha 35 04/13/2026
2.14.3-alpha 36 04/13/2026
2.14.2-alpha 36 04/13/2026
2.14.1-alpha 35 04/13/2026
2.14.0 31 04/13/2026
2.13.1 29 04/13/2026
2.12.0 33 04/13/2026
2.11.0 28 04/13/2026
2.10.0 31 04/13/2026
2.8.1 35 04/13/2026
2.8.0 33 04/13/2026
2.7.0 29 04/13/2026
2.6.1 32 04/13/2026
2.6.0.1 32 04/13/2026