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US 12,590,889 B2Granted
Outlier detection for spectroscopic classification
AssigneeViavi Solutions Inc.
InventorsChang Meng Hsiung, Lan Sun
Life of this patent
Estimating the term…
Abstract
In some implementations, a device may determine that an unknown sample is an outlier sample by using an aggregated classification model. The device may determine that one or more spectroscopic measurements are not performed accurately based on determining that the unknown sample is the outlier sample. The device may cause one or more actions based on determining the one or more spectroscopic measurements are not performed accurately.
Claims20
A method, comprising:
- receiving, by a device that includes a processor, information identifying results of a set of spectroscopic measurements of a training set of known samples and a validation set of known samples;
- causing, by the device, one or more spectrometers to perform one or more spectroscopic measurements of an unknown sample;
- receiving, by the device and based on causing the one or more spectrometers to perform the one or more spectroscopic measurements of the unknown sample, information identifying a result of the one or more spectroscopic measurements of the unknown sample;
- and
- causing, by the device, one or more actions based on a local classification model indicating that the unknown sample is an outlier sample,
- the local classification model being based on an aggregated classification model and the result of the one or more spectroscopic measurements of the unknown sample, and
- the aggregated classification model being based on the information identifying the results of the set of spectroscopic measurements of the training set and the validation set.
4 more elements
A system, comprising:
- one or more memories;
- and
- one or more processors, coupled to the one or more memories, configured to:
- receive information identifying results of a set of spectroscopic measurements;
- cause one or more spectrometers to perform one or more spectroscopic measurements of an unknown sample;
- receive, based on the one or more spectrometers being caused to perform the one or more spectroscopic measurements of the unknown sample, information identifying a result of the one or more spectroscopic measurements of the unknown sample;
- and
- cause one or more actions based on a local classification model indicating that the unknown sample is an outlier sample,
- the local classification model being based on an aggregated classification model and the result of the one or more spectroscopic measurements of the unknown sample, and
- the aggregated classification model being based on the information identifying the results of the set of spectroscopic measurements.
7 more elements
A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:
- one or more instructions that, when executed by one or more processors, cause the one or more processors to:
- receive information identifying results of a set of spectroscopic measurements of a training set of known samples and a validation set of known samples;
- cause one or more spectrometers to perform one or more spectroscopic measurements of an unknown sample;
- receive, based on the one or more spectrometers being caused to perform the one or more spectroscopic measurements of the unknown sample, information identifying a result of the one or more spectroscopic measurements of the unknown sample;
- and
- cause one or more actions based on a local classification model indicating information regarding the unknown sample,
- the local classification model being based on an aggregated classification model and the result of the one or more spectroscopic measurements of the unknown sample, and
- the aggregated classification model being based on the information identifying the results of the set of spectroscopic measurements of the training set and the validation set.
5 more elements
Dependencies are inferred from the claim text.