Classification, which is the task of assigning objects to one of several predefined
categories, is a pervasive problem that encompasses many diverse applications.
Examples include detecting spam email messages based upon the message
header and content, categorizing cells as malignant or benign based upon the
results of MRI scans, and classifying galaxies based upon their shapes.
This chapter introduces the basic concepts of classification, describes some
of the key issues such as model overfitting, and presents methods for evaluating
and comparing the performance of a classification technique. While it focuses
mainly on a technique known as decision tree induction, most of the discussion
in this chapter is also applicable to other classification techniques, many of
which are covered in Chapter 5.
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