Text Mining Algorithms
DOI:
https://doi.org/10.9734/bpi/mono/978-81-972870-5-3/CH9Keywords:
Text Mining Algorithms, Latent Dirichlet Allocation, K-Means Clustering, Naïve Bayes Classifier, Support Vector MachinesAbstract
This unit emphasizes exploring various text mining algorithms that are used to extract valuable insights from a large corpus of text data. The algorithms discussed in this unit include Latent Dirichlet Allocation, K-Means Clustering, Genetic Algorithm, Naïve Bayes Classifier, Association Rules, K-Nearest Neighbor, Support Vector Machines, Neural Networks, Decision Trees and Generalized Linear Models. Additionally, this unit also covers some popular text mining classification algorithms and data mining algorithms, along with relevant examples to help you understand the practical applications of these algorithms.
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Published
2024-08-02
How to Cite
Adebola K. Ojo. (2024). Text Mining Algorithms. Text Mining Techniques With Applications, Edition 1, 96–103. https://doi.org/10.9734/bpi/mono/978-81-972870-5-3/CH9
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