Classification: Basic Concepts - Data Mining: Concepts and Techniques - page 387

8.6 Why is naıve Bayesian classification called “naıve”? Briefly outline the major ideas of
naıve Bayesian classification.
8.7 The following table consists of training data from an employee database. The data have
been generalized. For example, “31

35” for age represents the age range of 31 to 35.
For a given row entry, count represents the number of data tuples having the values for
department, status, age , and salary given in that row.

:::

department status age salary count

sales senior 31:::35 46K:::50K 30

sales junior 26 ::: 30 26K ::: 30K 40

sales junior 31 ::: 35 31K ::: 35K 40

systems junior 21:::25 46K:::50K 20

systems senior 31:::35 66K:::70K 5

systems junior 26 ::: 30 46K ::: 50K 3

systems senior 41 ::: 45 66K ::: 70K 3

marketing senior 36:::40 46K:::50K 10

marketing junior 31:::35 41K:::45K 4

secretary senior 46 ::: 50 36K ::: 40K 4

secretary junior 26 ::: 30 26K ::: 30K 6

Let status be the class label attribute.
(a) How would you modify the basic decision tree algorithm to take into consideration
the count of each generalized data tuple (i.e., of each row entry)?
(b) Use your algorithm to construct a decision tree from the given data.
(c) Given a data tuple having the values “systems,” “26 . . . 30,” and “46-50K” for the
attributes department, age , and salary , respectively, what would a naıve Bayesian
classification of the status for the tuple be?
8.8 RainForest is a scalable algorithm for decision tree induction. Develop a scalable naıve
Bayesian classification algorithm that requires just a single scan of the entire data set
for most databases. Discuss whether such an algorithm can be refined to incorporate
boosting to further enhance its classification accuracy.
8.9 Design an efficient method that performs effective naıve Bayesian classification over
an infinite data stream (i.e., you can scan the data stream only once). If we wanted
to discover the evolution of such classification schemes (e.g., comparing the classifica-
tion scheme at this moment with earlier schemes such as one from a week ago), what
modified design would you suggest?
8.10 Show that accuracy is a function of sensitivity and specificity , that is, prove Eq. (8.25).
8.11 The harmonic mean is one of several kinds of averages. Chapter 2 discussed how to
compute the arithmetic mean , which is what most people typically think of when they
compute an average. The harmonic mean , H , of the positive real numbers, x 1 , x 2 , ::: , x n ,