摘要:
A data processing apparatus includes: predicting means for calculating a prediction value of time series data with respect to input of the time series data using a prediction model for predicting the time series data; determining means for determining a target value of the time series data on the basis of the prediction value of the time series data; error calculating means for calculating an error of the prediction value relative to the target value; and retrieving means for retrieving error reduction data as input of the time series data to the prediction model for reducing the error of the prediction value.
摘要:
A learning device includes: a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of a pattern learning model that learns a pattern using input data; model parameter sharing means for causing two or more learning modules from among the plurality of learning modules to share the model parameters; module creating means for creating a new learning module corresponding to new learning data for learning the pattern when the new learning data are supplied as the input data; similarity evaluation means for evaluating similarities among the learning modules after the update learning is performed over all the learning modules including the new learning module; and module integrating means for determining whether to integrate the learning modules on the basis of the similarities among the learning modules and integrating the learning modules.
摘要:
A learning device, learning method, and program for learning a pattern are disclosed. A learning device includes: a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of a pattern learning model that learns a pattern using input data; model parameter sharing means for causing two or more learning modules from among the plurality of learning modules to share the model parameters; and sharing strength updating means for updating sharing strengths between the learning modules so as to minimize learning errors when the plurality of model parameters are updated by the update learning.
摘要:
A data processing apparatus includes: predicting means for calculating a prediction value of time series data with respect to input of the time series data using a prediction model for predicting the time series data; determining means for determining a target value of the time series data on the basis of the prediction value of the time series data; error calculating means for calculating an error of the prediction value relative to the target value; and retrieving means for retrieving error reduction data as input of the time series data to the prediction model for reducing the error of the prediction value.
摘要:
A device for implementing a pattern learning model, the device including a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of the pattern learning model that learns a pattern using input data. The device further including a model parameter sharing means for causing two or more learning modules from among the plurality of learning modules to share the model parameters; and a classification means for classifying the plurality of learning modules on the basis of the plurality of model parameters of each of the learning modules after the update learning.
摘要:
A learning device includes: a plurality of learning modules, each of which performs update learning to update a plurality of model parameters of a pattern learning model that learns a pattern using input data; model parameter sharing means for causing two or more learning modules from among the plurality of learning modules to share the model parameters; and classification means for classifying the plurality of learning modules on the basis of the plurality of model parameters of each of the learning modules after the update learning.
摘要:
A data processing device for processing time-sequence data includes a learning unit for performing self-organizing learning of a SOM (self-organization map) making up a hierarchical SOM in which a plurality of SOMs are connected so as to construct a hierarchical structure, using, as SOM input data which is input to the SOM, a time-sequence of node information representing a winning node of a lower-order SOM which is at a lower hierarchical level from the SOM.
摘要:
A data processing device for processing time-sequence data includes a learning unit for performing self-organizing learning of a SOM (self-organization map) making up a hierarchical SOM in which a plurality of SOMs are connected so as to construct a hierarchical structure, using, as SOM input data which is input to the SOM, a time-sequence of node information representing a winning node of a lower-order SOM which is at a lower hierarchical level from the SOM.
摘要:
An information processing device includes an obtaining unit to obtain two pieces of information that are targets for searching for connections; a connection searching unit to use an action model wherein the manner of obtaining, from input information, obtain related information that relates to the input information is modeled, and find connection information to connect the two pieces of information, thereby searching connections between the two pieces of information; and a search result output unit to output the search results of the connections between the two pieces of information.
摘要:
An information processing device includes an obtaining unit to obtain two pieces of information that are targets for searching for connections; a connection searching unit to use an action model wherein the manner of obtaining, from input information, obtain related information that relates to the input information is modeled, and find connection information to connect the two pieces of information, thereby searching connections between the two pieces of information; and a search result output unit to output the search results of the connections between the two pieces of information.