tf.contrib.layers.multi_class_target

tf.contrib.layers.multi_class_target(
    n_classes,
    label_name=None,
    weight_column_name=None
)

Defined in tensorflow/contrib/layers/python/layers/target_column.py.

See the guide: Layers (contrib) > Feature columns

Creates a _TargetColumn for multi class single label classification. (deprecated)

THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-12. Instructions for updating: This file will be removed after the deprecation date.Please switch to third_party/tensorflow/contrib/learn/python/learn/estimators/head.py

The target column uses softmax cross entropy loss.

Args:

  • n_classes: Integer, number of classes, must be >= 2
  • 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.

Returns:

An instance of _MultiClassTargetColumn.

Raises:

  • ValueError: if n_classes is < 2