Applied Machine Learning (Paperback)

Vijayaragavan P.

ISBN 10: 6208432111 / ISBN 13: 9786208432119

Published by LAP Lambert Academic Publishing, 2025

About this Item

Paperback. This study presents a hybrid model that leverages the strengths of K-means clustering and Support Vector Machines (SVM) for classifying online product reviews. K-means is used to group reviews into clusters, reducing data complexity and improving feature extraction. Subsequently, SVM is employed to classify the clustered data into positive, negative, or neutral sentiments. The combined approach enhances classification accuracy, reduces computational cost, and effectively handles large datasets. Experimental results demonstrate that the proposed model outperforms traditional standalone classifiers in terms of precision, recall, and overall accuracy. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9786208432119

Bibliographic Details

• Title: Applied Machine Learning (Paperback)
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2025
• Language: English
• ISBN 10: 6208432111
• ISBN 13: 9786208432119
• Binding: Paperback
• Condition: new

About this title

Synopsis

This study presents a hybrid model that leverages the strengths of K-means clustering and Support Vector Machines (SVM) for classifying online product reviews. K-means is used to group reviews into clusters, reducing data complexity and improving feature extraction. Subsequently, SVM is employed to classify the clustered data into positive, negative, or neutral sentiments. The combined approach enhances classification accuracy, reduces computational cost, and effectively handles large datasets. Experimental results demonstrate that the proposed model outperforms traditional standalone classifiers in terms of precision, recall, and overall accuracy.