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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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Choosing a classifier

These are just four of the most popular classifiers out there, but there are many more to choose from. Although some classification mechanisms perform better on some types of datasets than others, it can be hard to develop an intuition for exactly the ones they are suitable for. In order to help with this, we will be examining the efficacy of our four classifiers on four different two-dimensional made-up datasets—each with a vastly different optimal decision boundary. In doing so, we will learn more about the characteristics of each classifier and have a better sense of the kinds of data they might be better suited for.

The four datasets are depicted in Figure 9.11:

Figure 9.11: A plot depicting the class patterns of our four ...

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