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 )
Head for linear regression. (deprecated)
THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Please switch to tf.contrib.estimator.*_head.
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
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_nameand the default variable scope will be
link_fn: link function to convert logits to predictions. If provided, this link function will be used instead of identity.
An instance of
Head for linear regression.