Ensemble Classification Methods with Applications in R introduces the reader in the ensemble classifiers methods by showing the most used techniques. This book showd in an intuitive way how the ensemble classification has arisen as an extension of the individual classifiers, which are their basic characteristics and what kind of problems can emerge in its practice use. Therefore, this book is addressed to everyone interested in starting in these fields, especially students, teachers, researchers and people dealing with statistical classification.To achieve these goals, the work is structured in two really difference sections which contain a total of eleven chapters. The first section, with more theoretical contents, covers the four initial chapters, including the introduction. The second section, from the fifth chapter to the end, has a much more practical nature, illustrating with examples of business failure prediction, zoology, ecology, among others, how the previously studied techniques are applied.
This book employs use of the adabag package throughout.