Classification of categories
Classifies object into categories using one of the following models:
PLS-DA
SMICA
Machine Learning
Curve Separation
For more information on how to train a model see any the classification of nuts tutorials: Nut classification
Parameters
Model
Select the model created for the classification of the samples.
Category
Which category to apply the segmentation.
Classification type
Object average spectrum
Classifies the object by taking the average spectrum from all pixels included in the object.
Pixel class majority
Classifies the object by the majority of the pixels in the object.
Pixel prediction
✅ Includes prediction of each pixel and visualization of the pixel prediction on the object.
⬜ Do not include the prediction or visualization
Weights
Only applicable when Pixel class majority is selected
Decides the importance of the pixels for the classification using pixel class majority.