Online Program

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Friday, May 31
Machine Learning
Machine Learning E-Posters, II
Fri, May 31, 3:00 PM - 4:00 PM
Grand Ballroom Foyer

Clustering Chocolate Types: Dark, White, Milk and Fruit (305122)

*Kaitlyn Zhang, Stanford OHS 
Charles Chen, Applied Materials 
Mason Chen, Stanford OHS 

Keywords: STEAMS, Flavonoids, Chocolate, Statistics, Antioxidant, Clustering

The objectives of this paper are to use Multivariate Statistics to define a health biometric on choosing a healthy chocolate to patients with heart disease. Chocolate, made from cocoa beans, contains flavonoids which contain antioxidants. Flavonoids are the most abundant polyphenols in the human diet. Polyphenols have antioxidant properties which can prevent aging and is also beneficial to heart disease and diabetes patients. People with heart diseases should eat less of saturated fat, trans fat, sodium, and cholesterol. They should eat more dietary fiber. Cocoa flavanols promote healthy blood flow circulation from head to toe. The heart, brain, and muscle depend on a healthy circulatory system. Data has been collected on 20+ chocolate ingredient contents from 60+ different types of chocolate. Multivariate correlation study has found that (1) strong negative correlation between Cocoa and Sugar, and (2) a strong positive correlation between Dietary Fiber and Iron. Most dark chocolate contains more cocoa and less sugar. Dietary fiber and iron are high in correlation because of the high cocoa percent. Fruit Chocolate has more Vitamin C. The above two correlations can be further explained by conducting the Hierarchical Clustering Analysis on separating the Dark Chocolate, Milk Chocolate, White Chocolate and Fruit Chocolate. The Cocoa, Calcium, and Vitamin C are the deciding factors to separate these four Chocolates.