lib/rumale/decomposition/fast_ica.rb
# Fit the model with training data, and then transform them with the learned model.
#
# @overload fit_transform(x) -> Numo::DFloat
#   @param x [Numo::DFloat] (shape: [n_samples, n_features]) The training data to be used for fitting the model.
# @return [Numo::DFloat] (shape: [n_samples, n_components]) The transformed data
Fit the model with training data, and then transform them with the learned model.
Fit the model with training data and then transform them with the learned model .
def fit_transform(x, _y = nil)
        x = check_convert_sample_array(x)
        raise 'FastICA#fit_transform requires Numo::Linalg but that is not loaded.' unless enable_linalg?
        fit(x).transform(x)
      end
def fit_transform ( x , _y = nil ) x = check_convert_sample_array ( x ) raise 'FastICA#fit_transform requires Numo::Linalg but that is not loaded.' unless enable_linalg? fit ( x ) . transform ( x ) end
Fit the model with training data, and then transform them with the learned model.
Fit the model with training data and then transform them with the learned model .
[n_samples, n_components]) The transformed data
[ n_samples n_components ] ) The transformed data
Numo::DFloat
x
<not_specific>
_y
<not_specific>
overload
> Numo::DFloat @param x [Numo::DFloat] (shape: [n_samples, n_features]) The training data to be used for fitting the model.
> Numo :: DFloat @param x [ Numo :: DFloat ] ( shape : [ n_samples n_features ] ) The training data to be used for fitting the model .