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# tf.contrib.metrics.streaming_percentage_less

```tf.contrib.metrics.streaming_percentage_less(
values,
threshold,
weights=None,
metrics_collections=None,
name=None
)
```

See the guide: Metrics (contrib) > Metric `Ops`

Computes the percentage of values less than the given threshold.

The `streaming_percentage_less` function creates two local variables, `total` and `count` that are used to compute the percentage of `values` that fall below `threshold`. This rate is weighted by `weights`, and it is ultimately returned as `percentage` which is an idempotent operation that simply divides `total` by `count`.

For estimation of the metric over a stream of data, the function creates an `update_op` operation that updates these variables and returns the `percentage`.

If `weights` is `None`, weights default to 1. Use weights of 0 to mask values.

#### Args:

• `values`: A numeric `Tensor` of arbitrary size.
• `threshold`: A scalar threshold.
• `weights`: An optional `Tensor` whose shape is broadcastable to `values`.
• `metrics_collections`: An optional list of collections that the metric value variable should be added to.
• `updates_collections`: An optional list of collections that the metric update ops should be added to.
• `name`: An optional variable_scope name.

#### Returns:

• `percentage`: A `Tensor` representing the current mean, the value of `total` divided by `count`.
• `update_op`: An operation that increments the `total` and `count` variables appropriately.

#### Raises:

• `ValueError`: If `weights` is not `None` and its shape doesn't match `values`, or if either `metrics_collections` or `updates_collections` are not a list or tuple.