API Reference¶
If you would like to use sklvq algorithms the most relevant part to look at is the “Predictors and Transformers” section. However, the other sections provide information about accepted parameters their range and default values.
Predictors and Transformers¶
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Learning Vector Quantization base class |
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Generalized Learning Vector Quantization |
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Generalized Matrix Learning Vector Quantization |
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Localized Generalized Matrix Learning Vector Quantization |
Objective Functions¶
Generalized learning objective |
Activation Functions¶
Activation base class |
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Identity function |
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Sigmoid function |
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Soft+ function |
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Swish function |
Distance Functions¶
Distance base class |
Euclidean distance function |
Squared Euclidean distance |
Adaptive squared Euclidean distance |
Local adaptive squared Euclidean distance |
Solvers¶
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Solver base class |
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Steepest gradient descent (SGD) |
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Waypoint gradient descent (WGD) |
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Adaptive moment estimation (ADAM) |
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Broyden Fletcher Goldfarb Shanno (BFGS) |
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Limited memory variant of BFGS (L-BFGS) |