class ConvNetLayer_2D extends AnyRef
The ConvNetLayer_2D
class implements a Convolutionsl Net Layer, meant to be
part of Convolutionsl Net classifier. The classifier is trained using a data
tensor 'x' and a classification vector 'y'.
Each row in the tensor is classified into one of 'k' classes numbered '0, ...0, k-1'.
Each column, depth in the tensor represents a 2D structure (e.g., an image).
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ConvNetLayer_2D(x: Tensor3D, y: VectoI, nf: Int = 5, height: Int = 5, width: Int = 5)
- x
the input/data 3D tensor with instances stored in rows
- y
the response/classification vector, where y_i = class for row i of matrix x
- nf
the number of filters for this convolutional
- height
the height of the filters
- width
the width of the filters
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def
filter(i: Int, f: Int): MatriD
Filter the 'i'-th input matrix with the 'f'-th filter.
Filter the 'i'-th input matrix with the 'f'-th filter.
- i
the index of the 'i'th row of the tensor
- f
the index of the 'f'th filter
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def
updateFilterParams(f: Int, mat2: MatriD): Unit
Update filter 'f's parameters.
Update filter 'f's parameters.
- f
the index for the filter
- mat2
the new paramters for the filter's matrix
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