tf.contrib.learn.binary_svm_head

tf.contrib.learn.binary_svm_head(
    label_name=None,
    weight_column_name=None,
    enable_centered_bias=False,
    head_name=None,
    thresholds=None
)

Defined in tensorflow/contrib/learn/python/learn/estimators/head.py.

Creates a Head for binary classification with SVMs. (deprecated)

THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Please switch to tf.contrib.estimator.*_head.

The head uses binary hinge loss.

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.
  • 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.
  • thresholds: thresholds for eval metrics, defaults to [.5]

Returns:

An instance of Head for binary classification with SVM.