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.