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0. Cross validation is a model evaluation method. Leave-one-out cross validation (LOOCV) is K-fold cross validation taken to its logical extreme, with K equal to N, the number of data points in the set. That means that N separate times, the function approximator is trained on all the data except for one point and a prediction is made for that point. Thus, it iterates over the other datapoints keeping the rest of the dataset fixed. What can be the major issues in LOOCV?
a. low variance
b. high variance
c. faster run time compared to K-fold cross validation
d. Slover run time compared to K-fold cross validation

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