Applied Machine Learning

Vijayaragavan P

ISBN 10: 6208432111 / ISBN 13: 9786208432119

Editore: LAP LAMBERT Academic Publishing Feb 2025, 2025

Riguardo questo articolo

Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 172 pp. Englisch.

Codice articolo 9786208432119

Dati bibliografici

• Titolo: Applied Machine Learning
• Editore: LAP LAMBERT Academic Publishing Feb 2025
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 6208432111
• ISBN 13: 9786208432119
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 220 L x 150 A x 11 P (millimetri) 220 millimetri di larghezza per 150 millimetri di altezza per 11 millimetri di profondità
• Peso: 274 grammi

Descrizione articolo

Riassunto

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.