# Data Mining 36

### Question Description

8. Discuss why a document-term matrix is an example of a data set that has asymmetric discrete or asymmetric continuous features.

10. Discuss the difference between the precision of a measurement and the terms single and double precision, as they are used in computer science, typically to represent floating-point numbers that require 32 and 64 bits, respectively.

22. Discuss how you might map correlation values from the interval [-1,1] to the interval [0,1]. Note that the type of transformation that you use might depend on the application that you have in mind. Thus, consider two applications:clustering time series and predicting the behavior of one time series given another.

27. Show that the distance measure defined as the angle between two data vectors,x and y, satisfies the metric axioms given on page 70. Specifically, d(x, y) : arccos(cos(x,y)).

8. Discuss why a document-term matrix is an example of a data set that has asymmetric discrete or asymmetric continuous features.10. Discuss the difference between the precision of a measurement and the terms single and double precision, as they are used in computer science, typically to represent floating-point numbers that require 32 and 64 bits, respectively.22. Discuss how you might map correlation values from the interval [-1,1] to the interval [0,1]. Note that the type of transformation that you use might depend on the application that you have in mind. Thus, consider two applications:clustering time series and predicting the behavior of one time series given another.27. Show that the distance measure defined as the angle between two data vectors,x and y, satisfies the metric axioms given on page 70. Specifically, d(x, y) : arccos(cos(x,y)).