MACHINE LEARNING APPARATUS
A machine learning apparatus includes: an estimating unit estimating, for each of classes into which an element is classified, a likelihood indicating a probability of being classified into the class for an element contained in learning data based on a learning model; a loss value calculation unit calculating a loss value indicating a degree of error of the likelihood based on the likelihood for each class estimated by the estimating unit and a loss function; a weight calculation unit calculating a weight based on a comparison between a first likelihood for a first class to which the element is to be classified as true and a second likelihood for another class to which the element is not to be classified as true among the likelihoods calculated for the classes; and a machine learning unit causing the learning model to perform machine learning based on the loss value and the weight.
1 . A machine learning apparatus, comprising:
an estimating unit configured to estimate, for each of a plurality of classes into which an element is classified, a likelihood indicating a probability of being classified into the class for an element contained in learning data based on a learning model;
a loss value calculation unit configured to calculate a loss value indicating a degree of error of the likelihood based on the likelihood for each class estimated by the estimating unit and a predetermined loss function;
a weight calculation unit configured to calculate a weight based on a comparison result between a first likelihood for a first class to which the element is to be classified as true and a second likelihood for another class to which the element is not to be classified as true among the likelihoods calculated for the respective classes; and
a machine learning unit configured to cause the learning model to perform machine learning based on the loss value and the weight.
2 . The machine learning apparatus according to claim 1 , wherein
the weight calculation unit calculates the weight based on the comparison result between the first likelihood and the second likelihood which is the highest among the likelihoods for the other classes.
3 . The machine learning apparatus according to claim 1 , wherein
the weight calculation unit calculates the weight further based on a difference between the first likelihood and the second likelihood.
4 . The machine learning apparatus according to claim 3 , wherein
the weight calculation unit calculates the weight W by substituting a difference value p between the first likelihood and the second likelihood, and a predetermined value y into the following equation (1)
W =−(1− p ) y log( p ) (1).
5 . The machine learning apparatus according to claim 1 , wherein
when the second likelihood is larger than the first likelihood, the weight calculation unit sets, as the weight, a value larger than that of a weight calculated when the first likelihood is larger than the second likelihood.