VectorDistance Examples Input - Teradata Vantage

Raw Input

The CallDuration values are so much higher than other attribute values that they skew the distribution. Normalizing the raw data to the range [0, 1] solves this problem.

Normalized Input

In the following table, the raw input data has been normalized to the range [0, 1] using the Min-Max normalization technique.

This technique transforms the value 'a' (in column A) to the value 'b' in the range [C, D], using this formula:

b=((a-minimum_value_in_A)/(maximum_value_in_A-minimum_value_in_A))*(D-C)+C

The following table shows the minimum and maximum values that the formula uses for each input table column.

From the normalized input data, select one or more users as the reference vector; the remaining users are the target vectors. The choice of reference vector depends on the application. For example, if the mobile telephone service is expanding its range to include a new area with similar users, then one or more typical users (with average or median attribute values) can be the reference vector. When the company has identified similar users in the new area, it can send them promotional offers.

Reference and Target Tables for Examples

For these examples, the reference vector is UserID 5.