redwine.txt

Assignment Tasks

$1.$ Understand the data

$($i$)$ Import the txt file $($RedWine$.$txt$)$ and save it to your R working directory.

$($ii$)$ Assign the data to a matrix, e$.$g$.$ using

the.data $<-$ as$.$matrix$($read$.$table$("$RedWine$.$txt $"))$

$($iii$)$ The variable of interest is quality $($Y$).$ To investigate Y$,$ generate a subset of $500$ data,

e$.$g$.$ using:

my$.$data $<-$ the.data$[$sample$(1$:$1599,400),$c$(1$:$6)]$

$[$The following tasks are based on the $400$ sample data$]$

$($iv$)$ Using scatter plots and histograms to understand the relationship between each of the

variables X$1,$ X$2,$ X$3,$ X$4,$ X$5$ and the variable of interest Y$.$

$2.$ Transform the data

Choose any four from the five variables $($X$1,$ X$2,...,$ X$5).$ Make appropriate

transformations to the chosen four variables and the variable of interest Y individually, so

that the values can be aggregated in order to predict the variable of interest.

Assign your transformed data along with your transformed variable of interest to an array.

$[$All the following tasks are based on the saved transformed data$]$

$3.$ Build models and investigate the importance of each variable

$($i$)$ Import AggWaFit$718.$R file to your working directory and load into the R workspace

using, source$("$AggWaFit$718.$R$")$

$($ii$)$ Evaluating the following fitting functions on the transformed data:

$$ A weighted arithmetic mean $($WAM$)$

$$ Weighted power means $($WPM$)$ with P$=0\mathrm{.}5$ and P$=2$

$$ An ordered weighted averaging function $($OWA$)$

$4.$ Use your model for prediction

Using your best fitting model based on Q$3,$ predict the wine quality for the input: X$1=1$;

X$2=0\mathrm{.}75$; X$3=40$; X$4=3\mathrm{.}53$; X$5=8\mathrm{.}3.$

$[$Apply the same pre$-$process as Q$2$ for the new input$]$

$2$

$3.$