Preprocessiterator
From Eigenvector Documentation Wiki
Contents |
Purpose
Create array of preprocessing combinations for use with modeloptimizer.
Synopsis
- pplist = preprocessiterator(inpp);%Shows gui for iterator settings.
- pplist = preprocessiterator(inpp,imatrix);%Command line call.
Description
For given input preprocessing structure (inpp), create combinations of preprocessing based on PP methods that can be iterated over using simple min/steps/max values. If iteration matrix (imatrix) is not provided a window will appear allowing user to specify iterations. Some of the methods are discussed in Advanced Preprocessing.
Supported Preprocessing Methods:
- Derivative (Savgol)
- Normalize
- GLS Weighting
- EPO Filter
- Baseline (Automatic Whittaker Filter)
- Detrend
- Gap Segment Derivative
- Autoscale
- Poisson (Sqrt Mean) Scaling
Iterator Matrix (imatrix) example. Cell array n x 9 with following columns:
- Relative Index - Relative index of given method.
- Preprocess Name - Name of preprocess method.
- Parameter Name - Name of .userdata parameter.
- Parameter Variable - Name of .userdata field.
- Data Type - Allowed values for Min and Max.
- Min - First value.
- Step - Size of interval of each step.
- Max - Last value.
- Use Log - Use a log scale to create values.
inpp = preprocess('default','mean center','derivative','normalize', 'mean center','sqmnsc','normalize','log10','whittaker'); imatrix = { 1 'derivative' 'Width' 'width' 'int(1:inf)' 1 1 1 0; 1 'derivative' 'Derivative' 'deriv' 'int(1:inf)' 1 1 1 0;... 1 'derivative' 'Order' 'order' 'int(1:inf)' 1 1 1 0; 2 'Normalize' 'Norm Type' 'normtype' 'int(1:inf)' 1 2 2 0;... 1 'GLS Weighting' 'Alpha' 'a' 'float(0:inf)' 1 1 1 1}; pplist = preprocessiterator(inpp,imatrix)
NOTE: If the original preprocess structure contains 2 Normalize steps, the second Normalize will be iterated over.