# SetClassifierTrainingOption

Sets the value of a training option that is applied to a classifier.

You can set the following training options:

Key | Description | Default
--- | --- | ---
`batchsize` | The number of images to train concurrently. The value must be 1,2,4,8,16, or 32. Larger batch sizes result in slightly faster training but require more memory (more GPU memory if you are training with a GPU). If you are training with a GPU that has limited memory you might need to reduce the batch size. | 32
`iterations` | The number of training iterations to perform. A larger number of iterations can result in more accurate classification, especially for classifiers that contain many similar classes. | 500
`snapshot_frequency` | The number of training iterations to perform before taking a snapshot of the classifier. For example, if you run 1000 iterations you might take snapshots every 250 iterations, so that there are snapshots for 250, 500, 750, and 1000 iterations. Taking snapshots can help you find the optimum number of iterations. | No snapshots
`validation_proportion` | The proportion of your training images to set aside to evaluate the performance of classifier snapshots. Specify a number between 0 and 1. The default value uses 75% of your images for training and 25% for evaluation. Unless you set `snapshot_frequency`, all images are used for training and none for evaluation. | 0.25

NOTE: Changing a training option invalidates all training associated with a classifier. After using this action, you must retrain Media Server by running the action BuildClassifier.

Type: synchronous

Parameter | Description | Required
--- | --- | ---
`classifier` | The name of the classifier to configure. | Yes
`key` | The name of the training option to set. | Yes
`value` | The value for the training option. | Yes

## Example

This example sets the `iterations` training option to `250`:

    /action=SetClassifierTrainingOption&classifier=vehicles
                                       &key=iterations
                                       &value=250

## Response

    <autnresponse>
       <action>SETCLASSIFIERTRAININGOPTION</action>
       <response>SUCCESS</response>
       <responsedata></responsedata>
    </autnresponse>

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