Titlebook: An Introduction to Machine Learning; Miroslav Kubat Textbook 20172nd edition Springer International Publishing AG 2017 Bayesian classifier

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https://doi.org/10.1007/978-3-476-05629-0The fundamental problem addressed by this book is how to induce a classifier capable of determining the class of an object. We have seen quite a few techniques that have been developed with this in mind.

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Probabilities: Bayesian Classifiers,The earliest attempts to predict an example’s class based on the known attribute values go back to well before World War II—prehistory, by the standards of computer science. Of course, nobody used the term “machine learning,” in those days, but the goal was essentially the same as the one addressed in this book.

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Inter-Class Boundaries: Linear and Polynomial Classifiers,When representing the training examples with points in an .-dimensional instance space, we may realize that positive examples tend to be clustered in regions different from those occupied by negative examples. This observation motivates yet another approach to classification.

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