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tf.contrib.learn.regression_head

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Creates a Head for linear regression. (deprecated)

tf.contrib.learn.regression_head(
    label_name=None,
    weight_column_name=None,
    label_dimension=1,
    enable_centered_bias=False,
    head_name=None,
    link_fn=None
)

Args:

  • label_name: String, name of the key in label dict. Can be null if label is a tensor (single headed models).
  • weight_column_name: A string defining feature column name representing weights. It is used to down weight or boost examples during training. It will be multiplied by the loss of the example.
  • label_dimension: Number of regression labels per example. This is the size of the last dimension of the labels Tensor (typically, this has shape [batch_size, label_dimension]).
  • enable_centered_bias: A bool. If True, estimator will learn a centered bias variable for each class. Rest of the model structure learns the residual after centered bias.
  • head_name: name of the head. If provided, predictions, summary and metrics keys will be suffixed by "/" + head_name and the default variable scope will be head_name.
  • link_fn: link function to convert logits to predictions. If provided, this link function will be used instead of identity.

Returns:

An instance of Head for linear regression.