(a). Produce conditional one-dimensional kernel-density estimates for each of the six ex- planatory variables (conditional on class labels). In each plot there will be three density estimates for the three classes. Comment on the implications for classifying the three classes. (b). Amalgamate the y = 1 and y = 2 classes into an “active” class. For each pair of explanatory variables make a plot like one demonstrated in the class (the image plot). This plot shows p(x|"Active") – p(x|"Inactive"). There are 15 possible plots; include only one you feel is most interesting and comment it.

MATLAB: An Introduction with Applications
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In this question, we will visualize the NIC Antivirus AIDS data. (Please solve this question using R code)

(a). Produce conditional one-dimensional kernel-density estimates for each of the six ex-
planatory variables (conditional on class labels). In each plot there will be three density
estimates for the three classes. Comment on the implications for classifying the three
classes.
(b). Amalgamate the y = 1 and y = 2 classes into an “active” class. For each pair of
explanatory variables make a plot like one demonstrated in the class (the image plot).
This plot shows p(x|"Active") – p(x|"Inactive"). There are 15 possible plots; include
only one you feel is most interesting and comment it.
Transcribed Image Text:(a). Produce conditional one-dimensional kernel-density estimates for each of the six ex- planatory variables (conditional on class labels). In each plot there will be three density estimates for the three classes. Comment on the implications for classifying the three classes. (b). Amalgamate the y = 1 and y = 2 classes into an “active” class. For each pair of explanatory variables make a plot like one demonstrated in the class (the image plot). This plot shows p(x|"Active") – p(x|"Inactive"). There are 15 possible plots; include only one you feel is most interesting and comment it.
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