Raw input data from sensors are preprocessed to obtain
a feature vector, x, that adequately describes
all of the relevant features for classifying examples.
Each x is a list of
(attribute, value) pairs. For example,
x = (Person = Sue, Eye-Color = Brown, Age = Young, Sex = Female)
The number of attributes (also called features)
is fixed (positive, finite).
Each attribute has a fixed, finite number of possible values.
Each example can be interpreted as a point in an
n-dimensional
feature space, where n is the number of attributes.
