# tf.raw_ops.BoostedTreesCenterBias

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Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior. Returns a boolean indicating whether to continue centering.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.BoostedTreesCenterBias`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/BoostedTreesCenterBias)

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    tf.raw_ops.BoostedTreesCenterBias(
        tree_ensemble_handle, mean_gradients, mean_hessians, l1, l2, name=None
    )

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| ## Args ||
|---|---|
| `tree_ensemble_handle` | A `Tensor` of type `resource`. Handle to the tree ensemble. |
| `mean_gradients` | A `Tensor` of type `float32`. A tensor with shape=\[logits_dimension\] with mean of gradients for a first node. |
| `mean_hessians` | A `Tensor` of type `float32`. A tensor with shape=\[logits_dimension\] mean of hessians for a first node. |
| `l1` | A `Tensor` of type `float32`. l1 regularization factor on leaf weights, per instance based. |
| `l2` | A `Tensor` of type `float32`. l2 regularization factor on leaf weights, per instance based. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| A `Tensor` of type `bool`. ||

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