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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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Chapter 4. Advanced Classification

In this chapter, you will learn about the top classification algorithms written in the R language. You will also learn the ways to improve the classifier.

We will cover the following topics:

  • Ensemble methods
  • Biological traits and Bayesian belief network
  • Protein classification and the k-Nearest Neighbors algorithm
  • Document retrieval and Support Vector Machine
  • Text classification using sentential frequent itemsets and classification using frequent patterns
  • Classification using the backpropagation algorithm

Ensemble (EM) methods

To improve the accuracy of classification, EM methods are developed. The accuracy is dramatically improved by at least one grade compared to its base classifiers, because the EM methods make mistakes ...

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