# Normalize the range such that the transformed range

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?