class_docstr: Implements the ESP kernel from Kandasamy, Yu 2016, 'Additive Approximations in High
  Dimensional Nonparametric Regression. 
class_docstr_tok: ["Implements","the","ESP","kernel","from","Kandasamy",",","Yu","2016",",","'Additive","Approximations","in","High","Dimensional","Nonparametric","Regression","."]
docstr: Evaluates SALSA on X_test.
      
docstr_tok: ["Evaluates","SALSA","on","X_test","."]
code: def eval(self, X_test):
      """Evaluates SALSA on X_test."""
      test_mean = self.mean_func(X_test)
      K_tetr = self.kernel(X_test, self.X)
      predictions = test_mean + K_tetr.dot(self.alpha)
      return predictions
  
imports: from __future__ import print_function
  import numpy
  from scipy.linalg import solve_triangular
label_desc: Use image node_id 4 for calling the SALSA obj's underlying member method code with example usage: obj.eval(X_test) and returns: predictions