idk good luck man idek if this is a question but if it is just go with c or b
Use the function varimp() on the output of train() and save it to an object called imp object.
<h3>What is the classification that has More than Two Classes and the Caret Package</h3>
In the Classification that has More than Two Classes and the Caret Package section, one need to use the methods that can be able to adapt to higher forms or dimensions and through a lot of different machine learning algorithms.
Note that varImp is seen as a generic method for calculating variable .
Hence, Use the function varimp() on the output of train() and save it to an object called imp object.
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Answer:
This is a multicolinearity problem and the student should determine the variable(s) that cause(s) the problem and remove it.
Explanation:
This information means that there exists a linear combination between the independent variables. The problem might have developed due to multicolinearity producing almost perfectly linearly dependent columns.
This could also be as a results of single matrix created when the student use an incorrect indicator variables and included an additional indicator column which created linearly dependent columns.
Probably providing a common calendar
