Question:
Suppose a group of 12 sales price records has been sorted as given:
5, 10, 11, 13, 15, 35, 50, 55, 72, 92, 204, 215.
Part 1: Partition them into three bins by each of the given methods.
(a) equal?frequency (equidepth) partitioning
(b) equal?width partitioning
Part 2: Normalize the range between [0, 1].
Part 3: Normalize the range such that the transformed range has a mean of 0 and a standard deviation of 1.
Question 2:
Design L1 and L2 distance functions to assess the dissimilarity of bank customers. Each customer is characterized by the subsequent attributes:
? SSN
? Cr ("credit rating") which is ordinal attribute with values 'very good', 'good, 'medium',
'poor', and 'very poor'.
? Av_bal (avg account balance, which is a real number with mean 7000, standard deviation is 4000, the maximum 3,000,000 and minimum ?20,000)
Part 1: Using the L1 distance function computes the distance between the subsequent 2 customers:
c1=(111111111, good, 7000) and c2=(222222222, poor, 1000).
Part 2: Using the L2 distance function computes the distance between the above mentioned 2 customers.
Can somebody provide the answer for given question with example?