Identification using spectroscopy

A computer-readable medium storing instructions, the instructions comprising:

• one or more instructions that, when executed by one or more processors, cause the one or more processors to:
• receive a global classification model from another device,
• the global classification model being distributed by the other device to a plurality of devices,
• the plurality of devices including the device, and
• the global classification model including a set of classes;
• receive information identifying results of a set of spectroscopic measurements of an unknown set,
• the unknown set including a plurality of unknown samples;
• perform a first classification of the plurality of unknown samples based on the results of the set of spectroscopic measurements and the global classification model,
• the global classification model utilizing a support vector machine (SVM) linear classifier technique;
• generate a set of local classification models for the plurality of unknown samples based on the first classification,
• the set of local classification models utilizing the SVM linear classifier technique, and
• the set of local classification models including a subset of classes of the set of classes of the global classification model;
• perform a second classification of the plurality of unknown samples based on the results of the set of spectroscopic measurements and the set of local classification models;
• and
• provide information identifying classifications of the plurality of unknown samples based on performing the second classification.

A method, comprising:

• receiving, by a device, a global classification model from another device,
• the global classification model being generated by the other device and being distributed to a plurality of devices,
• the plurality of devices including the device, and
• the global classification model including a set of classes;
• receiving, by the device, information identifying results of a spectroscopic measurement of an unknown sample performed by a first spectrometer;
• performing, by the device, a first classification of the unknown sample based on the results of the spectroscopic measurement and the global classification model,
• the global classification model being generated utilizing a support vector machine (SVM) classifier technique and a set of spectroscopic measurements performed by a second spectrometer associated with the other device;
• generating, by the device, a local classification model based on the first classification,
• the local classification model utilizing the SVM classifier technique, and
• the local classification model including a subset of classes of the set of classes of the global classification model;
• performing, by the device, a second classification of the unknown sample based on the results of the spectroscopic measurement and the local classification model;
• and
• providing, by the device, information identifying a class, of the subset of classes, associated with the unknown sample based on performing the second classification.