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Data Science Journal
The prediction of product acceptability is often an additive effect of individual fuzzy impressions developed by a consumer on certain underlying attributes characteristic of the product. In this paper, we present the development of a data-driven fuzzy-rule-based approach for predicting the overall sensory acceptability of food products, in this case composite cassava-wheat bread. The model was formulated using the Takagi-Sugeno and Kang (TSK) fuzzy modeling approach. Experiments with the modeldoi:10.2481/dsj.007-006 fatcat:zau4hlcvwrcdpeskrnzbphwrgi