| 摘要 |
<p><P>PROBLEM TO BE SOLVED: To provide a learning device for a pattern classification device for obtaining a high recognition rate by using a loss function directly connected to Bayesian error estimation. <P>SOLUTION: A learning device 42 includes: a storage device 64 for storing a learning pattern set; and a learning device 66 for learning a discriminant function to be defined for each class by a learning pattern. The discriminant function is expressed with the linear sum of kernel arithmetic operations between an input pattern and a plurality of prototypes. The kernel is defined by an internal product between an input pattern after conversion and the prototype after conversion in the case of determining characteristic conversion for converting the input pattern into a space whose dimension is higher than that of the space of the input pattern, and a gram matrix configured of the kernel arithmetic operations between the mutual prototypes is turned into a positive definite matrix. The learning device is configured to adjust a coefficient vector to minimize an average classification error number loss to be defined as a function between a learning pattern and a coefficient vector set in the high dimensional space. <P>COPYRIGHT: (C)2012,JPO&INPIT</p> |
