On characterization of sensory data in presence of missing values: The case of sensory coffee quality assessment

Multiple factor analysis was used to examine organoleptic coffee assessments such as aroma, aftertaste, flavor, acidity, balance, body, uniformity, sweetness, clean cup, and other organoleptic-related properties in Coffee Quality Assessment. The Sensory performed using missing values (NA) scenarios with 5%, 10%, 20%, 30% of NA. results suggest that RI-MFA is robust NA presence appears be appropriate when sensory data are present. Simulation deleting or replacing from real-world datasets could a good strategy; different domains, samples, types variables, distributions prove much closer reality.