WineData {NetDA}

Network-Based Discriminant Analysis Subject to Multi-Label Classes

Description

The dataset, available at https://archive.ics.uci.edu/ml/datasets/wine, illustrates the usage of NetDA and Metrics functions. The dataset contains measurements of 178 units where the response is classified as three classes together with 13 relevant predictors.

Usage

data(WineData)

Format

The dataset contains one response, 13 predictors, and 178 subjects.

Examples

Y = WineData[,1]     # the response
X = WineData[,2:14]  # the predictors

D1 = WineData[which(Y==1),]
D2 = WineData[which(Y==2),]
D3 = WineData[which(Y==3),]

Train = rbind(D1[1:45,], D2[1:45,],D3[1:45,])   # user-specific training data
Test = rbind(D1[45:dim(D1)[1],], D2[45:dim(D2)[1],],D3[45:dim(D3)[1],]) # user-specific testing data

X = Train[,2:14]
Y = Train[,1]
X_test = Test[,2:14]
Y_test = Test[,1]