LEARNING APPARATUS, PREDICTION APPARATUS, LEARNING METHOD, PREDICTION METHOD AND PROGRAM
A learning device for predicting an occurrence of an event includes a memory and a processor configured to divide a support set extracted from a set of previous data for learning into a plurality of sections, output a first latent vector based on each of the plurality of divided sections and output a second latent vector based on each of the output first latent vectors, and output an intensity function indicating a likelihood of the event occurring based on the second latent vector.
1 . A learning device for predicting an occurrence of an event, comprising:
a memory; and
a processor configured to:
divide a support set extracted from a set of previous data for learning into a plurality of sections;
output a first latent vector based on each of the plurality of divided sections and output a second latent vector based on each of the output first latent vectors; and
output an intensity function indicating a likelihood of the event occurring based on the second latent vector.
2 . The learning device according to claim 1 , the processor is further configured to:
update any parameter of a first model for outputting the first latent vector, a second model for outputting the second latent vector, and a third model for outputting the intensity function based on the intensity function.
3 . The learning device according to claim 1 , wherein the processor outputs the first latent vector based on each of the plurality of divided sections by parallel distributed processing.
4 . A predicting device for predicting an occurrence of an event, comprising:
a memory; and
a processor configured to:
divide a prediction target sequence into a plurality of sections by regarding the prediction target sequence as a support set;
output a first latent vector based on each of the plurality of divided sections and output a second latent vector based on each of the output first latent vectors; and
output an intensity function indicating a likelihood of the event occurring based on the second latent vector.
5 . The predicting device according to claim 4 , the processor is further configured to:
predict a situation of occurrences of events of an event in a prediction period using the intensity function.
6 . A learning method performed by a learning device including a memory and a processor, the method comprising:
dividing a support set extracted from a set of previous data for learning into a plurality of sections;
outputting a first latent vector based on each of the plurality of divided sections and outputting a second latent vector based on each of the output first latent vectors; and
outputting an intensity function which indicates a likelihood of an event occurring based on the second latent vector.
7 . (canceled)
8 . A non-transitory computer-readable recording medium having computer-readable instructions stored thereon, which, when executed, cause a computer including a memory and processor to function as the learning device according to claim 1 .
9 . A non-transitory computer-readable recording medium having computer-readable instructions stored thereon, which, when executed, cause a computer including a memory and processor to function as the predicting device according to claim 4 .