class_docstr: Factorization Machine (aka FM).
  
  This class implements L2-regularized arbitrary order FM model with MSE
  loss and gradient-based optimization.
  
  Custom loss functions are not supported, mean squared error is always
  used. Any loss function provided in parameters will be overwritten.
  
  See TFFMBaseModel and TFFMCore docs for details about parameters.
code: def __init__(self, **init_params):
      assert (
          "loss_function" not in init_params
      ), """Parameter 'loss_function' is
          not supported for TFFMRegressor. For custom loss function, extend the
          base class TFFMBaseModel."""
  
      init_params["loss_function"] = loss_mse
      self.init_basemodel(**init_params)
  
file_path: tffm/tffm/models.py
imports: import numpy
  from .base import TFFMBaseModel
  from .utils import loss_logistic, loss_mse, sigmoid
label_desc: Use image node_id 1 to create a new TFFMRegressor object from inherited base classes: TFFMBaseModel with example: obj = TFFMRegressor()