Class HLLENode

Keyword Arguments:

 k -- number of nearest neighbors to use; the node will raise
      an MDPWarning if k is smaller than
        k >= 1 + output_dim + output_dim*(output_dim+1)/2,
      because in this case a less efficient computation must be
      used, and the ablgorithm can become unstable
 r -- regularization constant; as opposed to LLENode, it is
      not possible to compute this constant automatically; it is
      only used during execution
 svd -- if True, use SVD to compute the projection matrix;
        SVD is slower but more stable
 verbose -- if True, displays information about the progress
            of the algorithm

 output_dim -- number of dimensions to output
               or a float between 0.0 and 1.0. In the latter case,
               output_dim specifies the desired fraction of variance
               to be exaplained, and the final number of output
               dimensions is known at the end of training
               (e.g., for 'output_dim=0.95' the algorithm will keep
               as many dimensions as necessary in order to explain
               95% of the input variance)                       

Overrides: object.__init__