Data processing device, data processing system, and data processing method

A data processing system, comprising:

• one or a plurality of processors,
• the processors being configured to acquire a plurality of first features corresponding to a first classification label and a plurality of second features corresponding to a second classification label,
• the processors being configured to select at least a part of the plurality of first features from the plurality of first features, being configured to select at least a part of the plurality of second features from the plurality of second features, and being configured to perform a first operation, in the first operation, a first number of the at least a part of the selected first features being not less than 1.1 times and not more than 2 times a second number of the at least a part of the selected second features,
• the processors being configured to generate a first machine learning model based on first training data based on the at least a part of the selected first features and the at least a part of the selected second features,
• the processors being configured to acquire a plurality of third features corresponding to the first classification label and a plurality of fourth features corresponding to the second classification label,
• the processors being configured to select at least a part of the plurality of third features from the plurality of third features, is configured to select at least a part of the plurality of fourth features from the plurality of fourth features, and the processors being configured to perform a second operation, in the second operation, a third number of the at least a part of the selected third features is not less than 0.1 times and not more than 0.9 times a fourth number of the at least a part of the selected fourth features, and
• the processors being configured to generate a second machine learning model based on second training data based on the at least a part of the selected third features and the at least a part of the selected fourth features, wherein
• generation of the first machine learning model includes a mapping operation of the at least a part of the selected first features and the at least a part of the plurality of second features to a feature space, and
• generation of the first machine learning model includes derivation of a first classifier of a quantity after the mapping operation, the first classifier relating to the first classification label and the second classification label.

A data processing method, comprising:

• causing a processor to acquire a plurality of first features corresponding to a first classification label and a plurality of second features corresponding to a second classification label;
• causing the processor to select at least a part of the plurality of first features from the plurality of first features and to select at least a part of the plurality of second features from the plurality of second features, and to perform a first operation, in the first operation, a first number of the at least a part of the selected first features being not less than 1.1 times and not more than 2 times a second number of the at least a part of the selected second features;
• and
• causing the processor to generate a first machine learning model based on a first training data based on the at least a part of the selected first features and the at least a part of the selected second features, wherein
• the method comprises
• causing the processor to acquire a plurality of third features corresponding to the first classification label and a plurality of fourth features corresponding to the second classification label,
• causing the processor to select at least a part of the plurality of third features from the plurality of third features, to select at least a part of the plurality of fourth features from the plurality of fourth features, and to perform a second operation, in the second operation, a third number of the at least a part of the selected third features is not less than 0.1 times and not more than 0.9 times a fourth number of the at least a part of the selected fourth features, and
• causing the processor to generate a second machine learning model based on second training data based on the at least a part of the selected third features and the at least a part of the selected fourth features,
• generation of the first machine learning model includes a mapping operation of the at least a part of the selected first features and the at least a part of the plurality of second features to a feature space, and
• generation of the first machine learning model includes derivation of a first classifier of a quantity after the mapping operation, the first classifier relating to the first classification label and the second classification label.