lib/rumale/kernel_approximation/nystroem.rb
# Transform the given data with the learned model.
#
# @param x [Numo::DFloat] (shape: [n_samples, n_features]) The data to be transformed with the learned model.
# @return [Numo::DFloat] (shape: [n_samples, n_components]) The transformed data.
Transform the given data with the learned model.
Transform the given data with the learned model .
def transform(x)
        x = check_convert_sample_array(x)
        z = kernel_mat(x, @components)
        z.dot(@normalizer)
      end
def transform ( x ) x = check_convert_sample_array ( x ) z = kernel_mat ( x , @components ) z . dot ( @normalizer ) end
Transform the given data with the learned model.
Transform the given data with the learned model .
[n_samples, n_components]) The transformed data.
[ n_samples n_components ] ) The transformed data .
Numo::DFloat
x
[n_samples, n_features]) The data to be transformed with the learned model.
[ n_samples n_features ] ) The data to be transformed with the learned model .