Model generation system, model generation method, and model generation program
AssigneeNEC Corporation
InventorsShinji Nakadai, Hao Zhang
Life of this patent
Estimating the term…
Abstract
The kernel function generation unit 81 defines a first kernel function by using two-dimensional feature representation that represents a combination of two features of data. The model learning unit 82 defines a linear model including an inner product of a mapping used in the first kernel function and a first weight and performs learning with the defined linear model. The component expanding unit 83 expands the learned linear model to define expanded component representation that is new component representation of the data. The expansion model generation unit 84 generates an expansion model including an inner product of data by the expanded component representation and a second weight.
Claims12
A model generation system, comprising:
- at least one processor;
- and
- at least one memory storing instructions that, when executed by the at least one processor, cause the processor to perform a method, the method comprising:
- defining a first kernel function by using two-dimensional feature representation that represents a combination of two features of data;
- defining a linear model including an inner product of a mapping used in the first kernel function and a first weight and performing learning with the defined linear model;
- expanding the learned linear model to define expanded component representation that is new component representation of the data;
- and
- generating an expansion model including an inner product of data by the expanded component representation and a second weight.
A model generation method, implemented by at least one processor executing program instructions stored in at least one memory, the method comprising:
- defining a first kernel function by using two-dimensional feature representation that represents a combination of two features of data;
- defining a linear model including an inner product of a mapping used in the first kernel function and a first weight and performing learning with the defined linear model;
- expanding the learned linear model to define expanded component representation that is new component representation of the data;
- and
- generating an expansion model including an inner product of data by the expanded component representation and a second weight.
A non-transitory computer readable information recording medium storing a model generation program, when executed by a processor, that performs a method for:
- defining a first kernel function by using two-dimensional feature representation that represents a combination of two features of data;
- defining a linear model including an inner product of a mapping used in the first kernel function and a first weight and performing learning with the defined linear model;
- expanding the learned linear model to define expanded component representation that is new component representation of the data;
- and
- generating an expansion model including an inner product of data by the expanded component representation and a second weight.
Dependencies are inferred from the claim text.