---
title: MeasureNoiseLearningOptions (latest version)
description: API reference for qiskit_ibm_runtime.options_models.MeasureNoiseLearningOptions in the latest version of qiskit-ibm-runtime
source: https://eu-de.quantum.cloud.ibm.com/docs/en/api/qiskit-ibm-runtime/options-models-measure-noise-learning-options
---

# qiskit\_ibm\_runtime.options\_models.MeasureNoiseLearningOptions

*pydantic model* `MeasureNoiseLearningOptions`

[GitHub](https://github.com/Qiskit/qiskit-ibm-runtime/tree/stable/0.50/qiskit_ibm_runtime/options_models/measure_noise_learning.py#L24-L37)

Bases: `BaseOptionsModel`

Options for measurement noise learning. This is only used by V2 Estimator.

> **Note**
>
> These options are only used when the resilience level or options specify a technique that requires measurement noise learning.

**Config**

- **validate\_assignment**: *bool = True*
- **extra**: *str = forbid*

### num\_randomizations

*field*

Type: `Annotated`\[`int`, `Field`(`ge``=``1`)] | `Literal`\[`'auto'`]

Default value: `'auto'`

The number of random circuits to draw for the measurement learning experiment.

If `"auto"`, the calibration uses the same number of randomizations as specified in the estimator’s twirling options.

### update

`update(**kwargs)`

[GitHub](https://github.com/Qiskit/qiskit-ibm-runtime/tree/stable/0.50/qiskit_ibm_runtime/options_models/base.py#L46-L54)

Update the options.

**Parameters**

**kwargs** (*Any*)

**Return type**

None