# Focused Mode Processing Parameters

The Processing parameters control the way that images are processed by the tool. Changing these parameters does not require the tool to be retrained; the effect can be seen right away by reprocessing the database.

Parameter | Description
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Sampling Density | Specifies the density of sampling points with respect to the tool's Feature Size (FS) setting. The sampling density determines the degree of overlap between adjacent samples. A sampling rate of 1 means that the sampling location is incremented by the feature size between samples. The default sampling rate for most tools is 3, which means that the sampling location is incremented by one third of the feature size. Tip: One key aspect of the Sampling Density parameter is the relationship between the tool's processing time and accuracy. A tool's processing time depends approximately quadratically to the Sampling Density (Sd) value. For example, a Sampling Density setting of 1 is approximately nine times faster than a setting of 3 (n2). While higher Sampling Density settings are more accurate, it significantly impacts the processing time of the tool.
Note: For the Green Classify Tool in Focused mode, there is a fixed limit to the number of samples that can be processed for a single runtime image, which is 50,000. The number of samples is determined by the Feature Size, the image size, and the Sampling Density, as shown in the following equation: If you have the Masking Mode parameter enabled, the sample count is reduced by the proportion of the pixels that are masked. When the combination of image size, Feature Size and Sampling Density settings exceeds the limit, the following error message may be displayed: Failed to process database sample 'image_file.name' (maximal number of samples exceeded, please reduce the sampling density, view size and/or feature size). In this event, consider options to reduce the number of pixels being processed, either through the use of a mask, focusing the ROI to specific areas or using a larger feature size setting.
Threshold | The Threshold parameter determines the minimum score that a view must have to be classified.