In homework exercises we wrote (at least I did, and posted it) a function gini(dataList) to return the

gini impurity index associated with a list of objects belonging to multiple classes.

Write a function entropy(dataList) to return the entropy of a list of class labels of objects.

Entropy = where the sum is over all the classes, and the are the probability (or

fraction ) of the ith class in the set.

Entropy of the list of labels: ['Apple', 'Grape', 'Apple', 'Apple', 'Grape', 'Orange', 'Grape'] should be

about 1.45

2. In homework exercises we wrote (at least I did, and posted it) a function gini(dataList) to return the gini impurity index associated with a list of objects belonging to multiple classes. Write a function entropy(dataList) to return the entropy of a list of class labels of objects. Entropy - E-pi* log2(Pi) where the sum is over all the classes, and the p; are the probability (or fraction of the in class in the set. Entropy of the list of labels: ('Apple', 'Grape', 'Apple', 'Apple', 'Grape', 'Orange', 'Grape') should be about 1.45