tf.contrib.learn.binary_svm_head

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

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

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.

Args