RandomFeature

class.RandomFourierFeature(d, D, W=None, b=None, kernel='G', gamma=1, device='cpu')

Description: Random Fourier feature.

Parameters:

  • d : int, Input space dimension

  • D : int, Feature space dimension

  • W : tensor, shape=(D,d), random feature parameter for cos(2Wx+b), default=None

  • b : tensor, shape=(D), random feature parameter for cos(2Wx+b), default=None

  • kernel : char, kernel to use; ‘G’, ‘L’, or ‘C’, default=’G’

  • gamma : float, kernel scale, default=1

  • device : char, device to use, “cpu” or “cuda”, default=”cpu”

Methods:

  • transform(x) Transform original data to random features.
    • Parameters:

      • x : tensor, shape=(n,d), data to be transformed

    • Returns:

      • result : tensor, shape=(n,D), random features

Example:

1from Multi_Layer_Kernel_Machine.RandomFeature import RandomFourierFeature
2rff=RandomFourierFeature(90,100,kernel='G',gamma=0.1,device="cpu")
3feature=rff.transform(nntrain_x)