# tf.contrib.learn.binary_svm_head

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/learn/python/learn/estimators/head.py#L351-L384) |

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
    )

> [!WARNING]
> **Warning:** 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.

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| ## Args ||
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| `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 \[.5\] |

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| ## Returns ||
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| An instance of `Head` for binary classification with SVM. ||

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