tf.contrib.learn.binary_svm_head( label_name=None, weight_column_name=None, enable_centered_bias=False, head_name=None, thresholds=None )
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.
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_nameand the default variable scope will be
thresholds: thresholds for eval metrics, defaults to [.5]
An instance of
Head for binary classification with SVM.
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.