Statistical results of classification using different methods.

Statistical results of classification using different methods.

<p>Statistical results of classification using different methods.</p>

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Bibliographic Details
Main Author:	Guanqun Wang (705958) (author)
Published:	2025
Subjects:	Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified principal component analysis div >< p cluster category centers analyzing complex datasets targeted marketing strategies enhances marketing efficiency various customer groups identify redundant noise identify potential features different customer types customer characteristic identification experimental results demonstrate digital marketing using customer segmentation process >- means clustering proposed model exhibits digital marketing clustering results >- means customer segmentation customer satisfaction accurately identify validated using clustering performance >- learning typical characteristics thereby facilitating test set strategic formulation significantly augments robust capabilities reinforcement learning q </ proposed method predominant tools paper proposes optimal number kaggle dataset k </ high degree elbow method distinct characteristics dimensionality reduction correlation matrix classification accuracy address challenges
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