Machine learning method and information processing apparatus
AssigneeFujitsu Limited
InventorThang Duy Dang
Life of this patent
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Abstract
An information processing apparatus enters a plurality of data samples individually to a machine learning model and extracts a plurality of features from the machine learning model. The information processing apparatus normalizes the plurality of features to a plurality of normalized features. The information processing apparatus selects, based on the plurality of normalized features, at least one data sample, which is part of the plurality of data samples, from the plurality of data samples. The information processing apparatus trains the machine learning model by using the at least one data sample.
Claims6
A non-transitory computer-readable recording medium storing therein a computer program that causes a computer to execute a process comprising:
- entering a plurality of data samples individually to a machine learning model and extracting a plurality of features of each of the data samples from the machine learning model;
- normalizing the plurality of features to a plurality of normalized features that fall within a certain numerical value range;
- selecting, based on the plurality of normalized features, at least one data sample, which is part of the plurality of data samples, from the plurality of data samples;
- and
- training the machine learning model by using the at least one data sample.
A machine learning method comprising:
- entering, by a processor, a plurality of data samples individually to a machine learning model and extracting a plurality of features of each of the data samples from the machine learning model;
- normalizing, by the processor, the plurality of features to a plurality of normalized features that fall within a certain numerical value range;
- selecting, by the processor, based on the plurality of normalized features, at least one data sample, which is part of the plurality of data samples, from the plurality of data samples;
- and
- training, by the processor, the machine learning model by using the at least one data sample.
An information processing apparatus comprising:
- a memory configured to store a plurality of data samples and a machine learning model;
- and
- a processor coupled to the memory and the processor configured to execute a process including:
- entering the plurality of data samples individually to the machine learning model,
- extracting a plurality of features of each of the data samples from the machine learning model,
- normalizing the plurality of features to a plurality of normalized features that fall within a certain numerical value range,
- selecting, based on the plurality of normalized features, at least one data sample, which is part of the plurality of data samples, from the plurality of data samples, and
- training the machine learning model by using the at least one data sample.
Dependencies are inferred from the claim text.