Figure 6
Transductive and inductive workflows. (A) The transductive workflow, in which all spectra are corrected at once, prior to partitioning the data into a training and testing set. (B) The inductive workflow, where the data are first partitioned and only the spectra in the training set are used to learn a transformation that is applied to all spectra. The dotted blue arrows show where the algorithms were applied on unseen data, while the whole black arrows show the workflow of the training data. Thus, in the inductive workflow, the test set is formed of unseen data that is only used for the final evaluation of the model. In the transductive case, some information is taken from all samples, while only the learning part of the workflow separating a test set on which the algorithm does not learn.
