INFORMATION PROCESSING DEVICE AND LEARNING METHOD
First Claim
1. An information processing device comprising:
- a data acquisition unit which acquires time-series data values for at least one of a prediction target type and another type that potentially affects the prediction target type; and
a prediction model learning unit which learns a prediction model including a first neural network and a second neural network to which subsets obtained by dividing a set that includes the time-series data values as elements are inputted respectively, and a third neural network to which an inner product of outputs from the first neural network and the second neural network is inputted and which outputs a predicted data value for the prediction target type as of a prediction target time.
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Abstract
An information processing device which generates a prediction model on time-series data by using neural networks in a short time is provided. A prediction model learning unit 121 learns a prediction model including a first neural network, a second neural network, and a third neural network. To the first neural network and a second neural network, subsets obtained by dividing a set that includes the time-series data values as elements are inputted respectively. To the third neural network, an inner product of outputs from the first neural network and the second neural network is inputted. The third neural network outputs a predicted data value for the prediction target type as of a prediction target time.
19 Citations
11 Claims
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1. An information processing device comprising:
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a data acquisition unit which acquires time-series data values for at least one of a prediction target type and another type that potentially affects the prediction target type; and a prediction model learning unit which learns a prediction model including a first neural network and a second neural network to which subsets obtained by dividing a set that includes the time-series data values as elements are inputted respectively, and a third neural network to which an inner product of outputs from the first neural network and the second neural network is inputted and which outputs a predicted data value for the prediction target type as of a prediction target time. - View Dependent Claims (2, 3, 4, 5)
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6. A learning method comprising:
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acquiring time-series data values for at least one of a prediction target type and another type that potentially affects the prediction target type; and learning a prediction model including a first neural network and a second neural network to which subsets obtained by dividing a set that includes the time-series data values as elements are inputted respectively, and a third neural network to which an inner product of outputs from the first neural network and the second neural network is inputted and which outputs a predicted data value for the prediction target type as of a prediction target time. - View Dependent Claims (7, 8)
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9. A non-transitory computer readable storage medium recording thereon a program, causing a computer to perform a method comprising:
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acquiring time-series data values for at least one of a prediction target type and another type that potentially affects the prediction target type; and learning a prediction model including a first neural network and a second neural network to which subsets obtained by dividing a set that includes the time-series data values as elements are inputted respectively, and a third neural network to which an inner product of outputs from the first neural network and the second neural network is inputted and which outputs a predicted data value for the prediction target type as of a prediction target time. - View Dependent Claims (10)
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11. An information processing device comprising:
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a data acquisition means for acquiring time-series data values for at least one of a prediction target type and another type that potentially affects the prediction target type; and a prediction model learning means for learning a prediction model including a first neural network and a second neural network to which subsets obtained by dividing a set that includes the time-series data values as elements are inputted respectively, and a third neural network to which an inner product of outputs from the first neural network and the second neural network is inputted and which outputs a predicted data value for the prediction target type as of a prediction target time.
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Specification