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in the figure 1
Features, The data set , made up of four families of features, is subdivided into four batches noted d1,d2,d3,d4.
Features Update and Backup, The update and save function allows first to recover one by one the copies of the di by concatenating them progressively. The updating of the features and the saving of the copy of the concatenation are carried out.
Data Pre-processing, The pre-processing stage cleans up the data, scales it and subdivides it into two groups: the training set and the test set.
Training and Model , This step allows to train algorithms in order to obtain a classification model
Testing and Predictions result ; In this step we test the performance of the obtained model with other data different from those used for training.
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IEEE/ICACT20220029 Slide.06
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