We know that headache may be caused by many different reasons. Suppose headache can only be caused by fever, anemia, cancer, and muscle pain, and we have a training dataset in which there are $100000$ samples and three independent attributes: weight, nutrition level, exercise degree. When applying Linear Discriminant Analysis $($LDA$),$ we know that the formula would be simplified to be: $Y=B+W1**$ weight $+W2**$ nutritionLevel $+$ W$3*$exerciseDegree$.$ After working with the training dataset, it was figured out that $B=100,W1=-0\mathrm{.}5,W2=5,W3=-2.$ In addition, the training dataset gives us further information as below if $Y>100,$ the reason is muscle pain

if $Y2020,$ the reason $is$ anemia

$ifY20,$ the reason $is$ fever

Now, $we$ have a patient who $is$ having a headache, and his weight $is200,$ his nutrition $is4,$ and his exercise level $is6.$ What reason will the LDA predict for this patient's headache?

fever

cancer

anemia

muscle pain$60,$ the reason $is$ cancer

$if20,$ the reason $is$ anemia

$ifY20,$ the reason $is$ fever

Now, $we$ have a patient who $is$ having a headache, and his weight $is200,$ his nutrition $is4,$ and his exercise level $is6.$ What reason will the LDA predict for this patient's headache?

fever

cancer

anemia

muscle pain