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# Priors

The probability that object classes will be seen in the media being analyzed. If you do not set this parameter, the image classification task expects that all of the classes are equally likely to be present in the media.

This parameter accepts a list of object class names mapped to floating point numbers. The numbers must be proportional to the prior probability that the object class will be seen. You must assign a value to every class that exists in the classifier.

Note: You can only use this parameter with Bayesian classifiers. The type of classifier is specified with the `ClassifierType` training option (see SetClassifierTrainingOption).

Type: | String (comma-separated list)
Default: |
Required: | No
Configuration Section: | TaskName
Example: | In the following example, the image classification task expects that more images or video frames will be classified as images of cars than other types of vehicle: `Priors=cars : 5,vans : 3, hgvs : 2` or
    Priors0=cars : 5
    Priors1=vans : 3
    Priors2=hgvs : 2
See Also: |

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