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.

Weights

Only applicable when Pixel class majority is selected

Decides the importance of the pixels for the classification using pixel class majority.

Pixel prediction

✅ Includes prediction of each pixel and visualization of the pixel prediction on the object.

⬜ Do not include the prediction or visualization

Connection

Only applicable for Hierarchical classification

Set parent class for hierarchical model.

Show Train/Test column in table

Adds an additional column in table showing if the object was part of Train or Test set

✅ Add Train/Test column

⬜ Do not add Train/Test column