class_docstr: 1D Kernel Density Regression/Kernel Smoother
  
  Requires:
  x - array_like of x values
  y - array_like of y values
  Kernel - Kernel object, Default is Gaussian.
class_docstr_tok: ["1D","Kernel","Density","Regression\/Kernel","Smoother","Requires",":","x","-","array_like","of","x","values","y","-","array_like","of","y","values","Kernel","-","Kernel","object",",","Default","is","Gaussian","."]
code: def __init__(self, x, y, Kernel=None):
      if Kernel is None:
          Kernel = kernels.Gaussian()
      self.Kernel = Kernel
      self.x = np.array(x)
      self.y = np.array(y)
  
file_path: statsmodels/statsmodels/sandbox/nonparametric/smoothers.py
imports: import numpy
  from .None import kernels
label_desc: Use image node_id 1 to create a new KernelSmoother object  with example: obj = KernelSmoother(x, y, Kernel)