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This book is concerned with numerical vector-based machine learning algorithms which are applied to index optimization. The book is authored by collecting slides about the application of machine learning algorithms to index optimization; each page is given as a slide. This book is intended for ones who study applications of machine learning algorithms to index optimization and is composed of five sections. Index optimization is defined as the process of classifying words into expansion, inclusion, and removal. This book covers the four machine learning algorithms, KNN Algorithm, Naïve Bayes, Learning Vector Quantization, and Perceptron, as approaches to index optimization.
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