67 lines
1.5 KiB
ReStructuredText
67 lines
1.5 KiB
ReStructuredText
.. Available Models
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Models
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========================================
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Unsupervised Methods
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.. autoclass:: prototorch.models.unsupervised.KNN
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:members:
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.. autoclass:: prototorch.models.unsupervised.NeuralGas
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:members:
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Classical Learning Vector Quantization
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Original LVQ models by Kohonen.
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These heuristic algorithms do not use gradient descent.
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.. autoclass:: prototorch.models.lvq.LVQ1
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:members:
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.. autoclass:: prototorch.models.lvq.LVQ21
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:members:
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It is also possible to use the GLVQ structure as shown in [Sato&Yamada].
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This allows the use of gradient descent methods.
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.. autoclass:: prototorch.models.glvq.GLVQ1
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:members:
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.. autoclass:: prototorch.models.glvq.GLVQ21
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:members:
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Generalized Learning Vector Quantization
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.. autoclass:: prototorch.models.glvq.GLVQ
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:members:
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.. autoclass:: prototorch.models.glvq.ImageGLVQ
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:members:
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.. autoclass:: prototorch.models.glvq.SiameseGLVQ
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:members:
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.. autoclass:: prototorch.models.glvq.GRLVQ
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:members:
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.. autoclass:: prototorch.models.glvq.GMLVQ
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:members:
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.. autoclass:: prototorch.models.glvq.LVQMLN
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:members:
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Classification by Component
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.. autoclass:: prototorch.models.cbc.CBC
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:members:
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.. autoclass:: prototorch.models.cbc.ImageCBC
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:members:
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Visualization
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========================================
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.. automodule:: prototorch.models.vis
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:members:
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:undoc-members: |