Classification:Basic Concepts,Decision Trees, and Model Evaluation.

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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