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Classification Analysis: Machine Learning Applied to Text
Book chapter

Classification Analysis: Machine Learning Applied to Text

Murugan Anandarajan, Chelsey Hill and Thomas Nolan
Practical Text Analytics, pp 131-149
20 Oct 2018
DOI: https://doi.org/10.1007/978-3-319-95663-3_9

Abstract

Artificial neural networks Categorization Classification analysis Decision trees Machine learning Naïve Bayes nearest neighbors Random forest Supervised learning Support vector machines Text categorization Text classification
This chapter introduces classification models. We begin with a description of the various measures for determining the model’s strength. Then, we explain popular classification models including Naïve Bayes, k-nearest neighbors, support vector machines, decision trees, random forests, and neural networks. We demonstrate the use of each model with the data from the example with the four dog breeds.

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