LEARNING DEVICE, ESTIMATION DEVICE, LEARNING METHOD, ESTIMATION METHOD, AND PROGRAM

1 . A apparatus that builds a model by performing machine learning, using, as training data, data detected by a plurality of types of sensors that detect a state of a subject, the apparatus comprising:

a normalizer-standardizer configured to perform normalization or standardization on data detected by the plurality of types of sensors; and

a learner configured to build the model by performing machine learning, using, as training data, the detected data on which normalization or standardization has been performed by the normalizer-standardizer, wherein the normalizer-standardizer performs normalization or standardization for each type of sensor, on data detected by the sensor.

2 . The apparatus according to claim 1 , wherein the plurality of types of sensors include a gravity sensor that detects a direction of gravity, the learning apparatus further comprises a corrector configured to correct data detected by a sensor that detects the state of the subject in a predetermined axis direction, other than the gravity sensor, of the plurality of types of sensors, based on data detected by the gravity sensor, and the normalizer-standardizer performs normalization or standardization on the detected data that has been corrected by the corrector.

3 . The apparatus according to claim 1 , wherein the apparatus estimates a state of a subject, using a model that has been built through machine learning performed using, as training data, data detected by a plurality of types of sensors that detect the state of the subject, the learning apparatus further comprising:

an estimator configured to estimate the state of the subject by applying the detected data on which normalization or standardization has been performed by the normalizer-standardizer, to the model, wherein the normalizer-standardizer performs normalization or standardization for each type of sensor, on data detected by the sensor.

4 . The apparatus according to claim 3 , wherein the plurality of types of sensors include a gravity sensor that detects a direction of gravity, the apparatus further comprises a corrector that corrects data detected by a sensor that detects the state of the subject in a predetermined axis direction, other than the gravity sensor, of the plurality of types of sensors, based on data detected by the gravity sensor, and the normalizer-standardizer performs normalization or standardization on the detected data that has been corrected by the corrector.

5 . (canceled)

6 . A method that is to be performed by an apparatus that estimates a state of a subject, using a model that has been built through machine learning performed using, as training data, data detected by a plurality of types of sensors that detect the state of the subject, the estimation method comprising:

performing, by a normalizer-standardizer, normalization or standardization on data detected by the plurality of types of sensors; and

estimating, by an estimator, the state of the subject by applying the detected data on which normalization or standardization has been performed, to the model, wherein, in the normalization/standardization step, normalization or standardization is performed for each type of sensor, on data detected by the sensor.

7 . A computer-readable non-transitory recording medium storing computer-executable instructions that when executed by a processor cause a computer system to:

perform, by a normalizer-standardizer, normalization or standardization on data detected by the plurality of types of sensors; and

perform, by a learner, machine learning, using, as training data, the detected data on which normalization or standardization has been performed, wherein the performing includes normalization or standardization of each type of sensor, on data detected by the sensor.

8 . The computer-readable non-transitory recording medium according to claim 7 , wherein the apparatus estimates a state of a subject, using a model that has been built through machine learning performed using, as training data, data detected by a plurality of types of sensors that detect the state of the subject, the computer-executable instructions when executed further causing the computer system to:

estimate, by an estimator, the state of the subject by applying the detected data on which normalization or standardization has been performed by the normalizer-standardizer, to the model, wherein the normalizer-standardizer performs normalization or standardization for each type of sensor, on data detected by the sensor.

9 . The method according to claim 6 associated with the apparatus that builds a model by performing machine learning, using, as training data, data detected by a plurality of types of sensors that detect a state of a subject, the method further comprising:

performing, by a learner, a learning step of building the model by performing machine learning, using, as training data, the detected data on which normalization or standardization has been performed, wherein the performing by the normalizer-standardizer includes normalization or standardization is performed for of each type of sensor, on data detected by the sensor.

10 . The method according to claim 6 , wherein the plurality of types of sensors include a gravity sensor that detects a direction of gravity, the method further comprising:

correcting, by a corrector, data detected by a sensor that detects the state of the subject in a predetermined axis direction, other than the gravity sensor, of the plurality of types of sensors, based on data detected by the gravity sensor; and

performing, by the normalizer-standardizer performs normalization or standardization on the detected data that has been corrected by the corrector.

11 . The method according to claim 9 , wherein the plurality of types of sensors include a gravity sensor that detects a direction of gravity, the method further comprising:

correcting, by a corrector, data detected by a sensor that detects the state of the subject in a predetermined axis direction, other than the gravity sensor, of the plurality of types of sensors, based on data detected by the gravity sensor; and

performing, by the normalizer-standardizer performs normalization or standardization on the detected data that has been corrected by the corrector.

12 . The computer-readable non-transitory recording medium of claim 7 , wherein the plurality of types of sensors include a gravity sensor that detects a direction of gravity, the computer-executable instructions when executed further causing the computer system to:

correct, by a corrector, data detected by a sensor that detects the state of the subject in a predetermined axis direction, other than the gravity sensor, of the plurality of types of sensors, based on data detected by the gravity sensor; and

perform, by the normalizer-standardizer performs normalization or standardization on the detected data that has been corrected by the corrector.

13 . The computer-readable non-transitory recording medium of claim 8 , wherein the plurality of types of sensors include a gravity sensor that detects a direction of gravity, the computer-executable instructions when executed further causing the computer system to:

correct, by a corrector, data detected by a sensor that detects the state of the subject in a predetermined axis direction, other than the gravity sensor, of the plurality of types of sensors, based on data detected by the gravity sensor; and

perform, by the normalizer-standardizer performs normalization or standardization on the detected data that has been corrected by the corrector.