Minimizemodel
Contents |
Purpose
Shrinks model by removing non-critical information.
Synopsis
- mm = minimizemodel(model) %compress model
- minimizemodel(model) %display size information only
Description
Models contain both the information necessary to apply that model to new data and also the results calculated with the model was built (such as scores, cross-validation results, Hotellings T^2, sum squared residuals from the calibration samples.) Although this additional calibration sample information is necessary to review the model results, they are not necessary to apply the model to new data.
MINIMIZEMODEL attempts to compress a model by removing the fields which are not strictly necessary to apply the model. Such compression will prevent the direct comparison of new sample results to calibration sample results, but the model will still be functional for on-line use, for example.
The extent of compression varies greatly between model types and will generally be more effective on models built from large numbers of samples and fewer variables as compared to models built from large numbers of variables and fewer samples.
If no outputs are requested, the sizes of all model fields with more than 100 bytes in size are returned.
Inputs
- model = standard model structure to compress.
Outputs
- mm = minimized model.