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 ...
© Danish Haroon 2017
Danish Haroon, Python Machine Learning Case Studies, https://doi.org/10.1007/978-1-4842-2823-4_5
5. Classification
Danish Haroon1
(1)Karachi, Pakistan
Get Python Machine Learning Case Studies: Five Case Studies for the Data Scientist now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
