FEATURE REDUCTION AND PREDICTION FOR WINE CHEMICAL COMPONENT USING PRINCIPAL COMPONENT ANALYSIS (PCA) AND LINEAR DISCRIMINANT ANALYSIS (LDA)

High dimensional data is frequently found in various field of study basically in the process of running data analysis; individuals have applied the various techniques available to manage high dimensional data. However, Principal Components Analysis (PCA) and Linear Discriminant Analysis(LDA) have been applied in high dimensional data, reducing the process of classifying features under consideration.