Importance

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Abstract

In some implementations, a device may receive a spectroscopic dataset associated with an unknown sample. The device may obtain a multiclass classification model to be used for classification of the unknown sample into at least one class of a plurality of classes; wherein the multiclass classification model comprises a plurality of local auto-scaled one-versus-one (OVO) binary classifiers, each local auto-scaled OVO binary classifier of the plurality of local auto-scaled OVO binary classifiers being associated with a different pair of classes from the plurality of classes. The device may apply local auto-scaling to the spectroscopic dataset associated with the unknown sample to create a local auto-scaled spectroscopic dataset. The device may perform a classification of the unknown sample based on the local auto-scaled spectroscopic dataset and using the multiclass classification model comprising the plurality of local auto-scaled OVO binary classifiers.

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