Apparatus for classifying data and method thereof

A computer-readable non-transitory recording medium having a program for executing a method on a computer, the method comprising:

• obtaining target data;
• obtaining first classification information by using a classifier set including a plurality of classifiers based on the target data;
• obtaining second classification information by using a neural network model based on the target data;
• comparing the first classification information and the second classification information;
• and
• verifying the classifier set based on a result of comparing the first classification information and the second classification information,
• wherein at least one of the first classification information and the second classification information includes a plurality of candidate classification values,
• wherein,
• if the second classification information includes the plurality of candidate classification values,
• the comparing the first classification information and the second classification information includes:
• determining one or more candidate classification values that satisfy a configured criterion among the plurality of candidate classification values included in the second classification information;
• and
• identifying whether each of the one or more candidate classification values matches a classification value indicated by the first classification information,
• wherein the configured criterion is a criterion related to probabilities that data belongs to each of the plurality of candidate classification values, and
• determining by the computer, scheduling of an operation performed by a core, among a plurality of cores of a processor, to be assigned to the operation for each of the plurality of classifiers based on each classifier requirements for an amount of computation needed for the operation and computing power of each of the plurality of cores.

A method for classifying data in an electronic apparatus, comprising:

• obtaining target data;
• obtaining first classification information by using a classifier set including a plurality of classifiers based on the target data;
• if the first classification information satisfies a configured condition, determining a classification value of the target data based on the first classification information;
• and
• if the first classification information does not satisfy the configured condition,
• obtaining second classification information by using a neural network model based on the target data;
• comparing the first classification information and the second classification information;
• and
• determining a classification value of the target data based on the second classification information,
• wherein at least one of the first classification information and the second classification information includes a plurality of candidate classification values,
• wherein,
• if the second classification information includes the plurality of candidate classification values,
• the comparing the first classification information and the second classification information includes:
• determining one or more candidate classification values that satisfy a configured criterion among the plurality of candidate classification values included in the second classification information;
• and
• identifying whether each of the one or more candidate classification values matches a classification value indicated by the first classification information,
• wherein the configured criterion is a criterion related to probabilities that data belongs to each of the plurality of candidate classification values, and
• determining by the electronic apparatus, scheduling of an operation performed by a core, among a plurality of cores of a processor, to be assigned to the operation for each of the plurality of classifiers based on each classifier requirements for an amount of computation needed for the operation and computing power of each of the plurality of cores.

An electronic apparatus for classifying data, comprising:

• a memory for storing instructions;
• and
• a processor,
• wherein the processor, being connected to the memory, is configured to:
• obtain target data;
• obtain first classification information by using a classifier set including a plurality of classifiers based on the target data;
• obtain second classification information by using a neural network model based on the target data;
• compare the first classification information and the second classification information;
• and
• verify the classifier set based on a result of comparing the first classification
• wherein at least one of the first classification information and the second classification information includes a plurality of candidate classification values,
• wherein,
• if the second classification information includes the plurality of candidate classification values,
• the comparing the first classification information and the second classification information includes:
• determining one or more candidate classification values that satisfy a configured criterion among the plurality of candidate classification values included in the second classification information;
• and
• identifying whether each of the one or more candidate classification values matches a classification value indicated by the first classification information,
• wherein the configured criterion is a criterion related to probabilities that data belongs to each of the plurality of candidate classification values, and
• determine by the electronic apparatus, scheduling of an operation performed by a core, among a plurality of cores of the processor, to be assigned to the operation for each of the plurality of classifiers based on each classifier requirements for an amount of computation needed for the operation and computing power of each of the plurality of cores.