class_docstr: Factorization Machine (aka FM).
  
  This class implements L2-regularized arbitrary order FM model with logistic
  loss and gradient-based optimization.
  
  Only binary classification with 0/1 labels supported.
  
  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 TFFMClassifier. For custom loss function, extend the
          base class TFFMBaseModel."""
  
      init_params["loss_function"] = loss_logistic
      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 TFFMClassifier object from inherited base classes: TFFMBaseModel with example: obj = TFFMClassifier()