抄録
Neural network as a data mining tool has a drawback in its black box nature, as the mechanism of relating the input and output parameter is not easily comprehensible by human. To extract the implicit knowledge from neural network in the form of if-then rules, the application of formal concept analysis is proposed. Using neural network trained with target data, a synthetic dataset of input and output is built and discretized to form a binary formal context. A formal concept analysis (In-Close) algorithm is applied to obtain formal concept, from where the implication rules are extracted. To show the effectiveness of the proposed method, an experiment is conducted using 480 data of six types of emotion and their corresponding HSV color components.
