Databases Reference
In-Depth Information
the patient undergoes a medical test that has two possible outcomes. The attribute
medical test
is binary, where a value of 1 means the result of the test for the patient
is positive, while 0 means the result is negative.
A binary attribute is
symmetric
if both of its states are equally valuable and carry
the same weight; that is, there is no preference on which outcome should be coded
as 0 or 1. One such example could be the attribute
gender
having the states
male
and
female
.
A binary attribute is
asymmetric
if the outcomes of the states are not equally impor-
tant, such as the
positive
and
negative
outcomes of a medical test for HIV. By convention,
we code the most important outcome, which is usually the rarest one, by 1 (e.g.,
HIV
positive
) and the other by 0 (e.g.,
HIV negative
).
2.1.4
OrdinalAttributes
An
ordinal attribute
is an attribute with possible values that have a meaningful order or
ranking
among them, but the magnitude between successive values is not known.
Example2.3
Ordinal attributes.
Suppose that
drink size
corresponds to the size of drinks available at
a fast-food restaurant. This nominal attribute has three possible values:
small, medium
,
and
large
. The values have a meaningful sequence (which corresponds to increasing
drink size); however, we cannot tell from the values
how much
bigger, say, a medium
is than a large. Other examples of ordinal attributes include
grade
(e.g.,
A
C
, A, A
, B
C,
and so on) and
professional rank
. Professional ranks can be enumerated in a sequential
order: for example,
assistant
,
associate
, and
full
for professors, and
private, private first
class, specialist, corporal, and sergeant
for army ranks.
Ordinal attributes are useful for registering subjective assessments of qualities that
cannot be measured objectively; thus ordinal attributes are often used in surveys for
ratings. In one survey, participants were asked to rate how satisfied they were as cus-
tomers. Customer satisfaction had the following ordinal categories:
0: very dissatisfied,
1: somewhat dissatisfied, 2: neutral, 3: satisfied
, and
4: very satisfied.
Ordinal attributes may also be obtained from the discretization of numeric quantities
by splitting the value range into a finite number of ordered categories as described in
Chapter 3 on data reduction.
The central tendency of an ordinal attribute can be represented by its mode and its
median (the middle value in an ordered sequence), but the mean cannot be defined.
Note that nominal, binary, and ordinal attributes are
qualitative
. That is, they
describe
a feature of an object without giving an actual size or quantity. The values of such
qualitative attributes are typically words representing categories. If integers are used,
they represent computer codes for the categories, as opposed to measurable quantities
(e.g., 0 for
small
drink size, 1 for
medium
, and 2 for
large
). In the following subsec-
tion we look at numeric attributes, which provide
quantitative
measurements of an
object.
