3:40 PM - 4:00 PM
[2E4-OS-9-02] A Multi-class Classification based on the Original Form of Kaomoji using Neural Network
Keywords:Kaomoji, Neural Network
In this paper, we propose a multi-class classification method for Kaomoji using feed-forward neural network.
Neural network has some units in each layer, but a suitable number of units is not precise.
This research investigated the relation between the number of units and the accuracy of the multi-class classification method. As a result, we found out the suitable number of units in a hidden layer is 6,500 based on a rule of thumb in our research.
Neural network has some units in each layer, but a suitable number of units is not precise.
This research investigated the relation between the number of units and the accuracy of the multi-class classification method. As a result, we found out the suitable number of units in a hidden layer is 6,500 based on a rule of thumb in our research.