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.