This head expects to be fed integer labels specifying the class index. But
if label_keys is specified, then labels must be strings from this
vocabulary, and the predicted classes will be strings from the same
Integer, number of classes, must be >= 2
String, name of the key in label dict. Can be null if label
is a tensor (single headed models).
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.
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.
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.
thresholds for eval metrics, defaults to [.5]
List of class IDs for which we should report per-class
metrics. Must all be in the range [0, n_classes). Invalid if
n_classes is 2.
Optional function that takes (labels, logits, weights) as
parameter and returns a weighted scalar loss. weights should be
optional. See tf.losses
Optional list of strings with size [n_classes] defining the
label vocabulary. Only supported for n_classes > 2.
An instance of Head for multi class classification.
if n_classes is < 2.
If metric_class_ids is provided when n_classes is 2.