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Published in:
2017 | OriginalPaper | Chapter
5. Classification
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Abstract
This chapter aims to solve real-world problems that depend on a finite number of outcomes. These outcomes can be Boolean in nature, with only two choices (i.e., True/False or Yes/No). They can also be nominal in nature (boat name on which a passenger will embark, maximum education attainment a group of students will have, etc.). Throughout this chapter we will be talking about supervised learning whereby labeled data will be used to train the model. Training the models on this data will enable label predictions on an unseen dataset (i.e., future predictions). In this chapter we will be talking about feature extraction and selection and will conclude with methods to evaluate classification accuracy.