tf.contrib.layers.multi_class_target( n_classes, label_name=None, weight_column_name=None )
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.
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.
An instance of _MultiClassTargetColumn.
ValueError: if n_classes is < 2