A calculation device includes an adding unit configured to add at least one new node to a network, which has multiple nodes that output results of calculations on input data are connected and which learned a feature of data belonging to a first subclass contained in a predetermined class. The calculation device includes an accepting unit configured to accept, as input data, training data belonging to a second subclass contained in the predetermined class. The calculation device includes a calculation unit configured to calculate coupling coefficients between the new node added by the adding unit and other nodes to learn a feature of the training data belonging to the second subclass based on an output result obtained when the training data accepted by the accepting unit is input to the network.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A calculation device comprising: an adding unit configured to add at least one new node to a network, which has multiple nodes that output results of calculations on input data are connected and which learned a feature of data belonging to a first subclass contained in a predetermined class; an accepting unit configured to accept, as input data, training data belonging to a second subclass contained in the predetermined class; and a calculation unit configured to calculate coupling coefficients between the new node added by the adding unit and other nodes to learn a feature of the training data belonging to the second subclass based on an output result obtained when the training data accepted by the accepting unit is input to the network. 2. The calculation device according to claim 1, wherein the calculation unit calculates coupling coefficients that minimize an error between the output result obtained when the training data is input to the network and a correct output result corresponding to the training data. 3. The calculation device according to claim 2, wherein the calculation unit calculates coupling coefficients between the new node added by the adding unit and the other nodes, that minimize the error, with stabilizing coupling coefficients between the other nodes. 4. The calculation device according to claim 2, wherein the calculation unit calculates the coupling coefficients between the new node added by the adding unit and the other nodes, that minimize the error, in order from a coupling coefficient with respect to a node located closest to an output layer among nodes contained in the network. 5. The calculation device according to claim 1, wherein the adding unit adds the new node to the network by setting the coupling coefficients between nodes contained in the network and the new node to initial values that do not influence to the output result. 6. The calculation device according to claim 1, further comprising: an output unit configured to output the coupling coefficients calculated by the calculation unit as a vector indicating a feature amount of the training data. 7. The calculation device according to claim 1, further comprising: an output unit configured to output a network, to which the new node is added and in which coupling coefficients between each of nodes are set to the coupling coefficients calculated by the calculation unit. 8. A calculation method implemented by a calculation device, the calculation method comprising: adding at least one new node to a network, which has multiple nodes that output results of calculations on input data are connected and which learned a feature of data belonging to a first subclass contained in a predetermined class; accepting, as input data, training data belonging to a second subclass contained in the predetermined class; and calculating coupling coefficients between the new node added at the adding and other nodes to learn a feature of the training data belonging to the second subclass based on an output result obtained when the training data accepted at the accepting is input to the network. 9. A non-transitory recording medium storing a calculating program causing a computer to execute calculating process, the calculating process comprising: adding at least one new node to a network, which has multiple nodes that output results of calculations on input data are connected and which learned a feature of data belonging to a first subclass contained in a predetermined class; accepting, as input data, training data belonging to a second subclass contained in the predetermined class; and calculating coupling coefficients between the new node added at the adding and other nodes to learn a feature of the training data belonging to the second subclass, based on an output result obtained when the training data accepted at the accepting is input to the network.