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Experimental Analysis of Machine Learning Algorithms in Classification Task of Mobile Network Providers in Virudhunagar District

  • A. RajeshkannaEmail author
  • V. Preetha
  • K. Arunesh
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 3)

Abstract

Data mining has many classification algorithms with desired features. The machine learning algorithms such as K Nearest Neighbor, Support Vector Machines and Neural Network are some of the most popular algorithms used for classification task. Since classification is gaining importance due to the enormous amount of big data in real world datasets, the choice of a perfect classification algorithm is an ultimate need. For the classification task, the “Mobile Phone network satisfaction” real world dataset has been collected from the mobile phone users. In today’s world, mobile network chosen by the users has a greater impact on the individual user’s day-to-day activities and also on the business of network providers. Hence, the performance and accuracy of the mentioned machine learning algorithms has been investigated and analyzed in the prior described datasets. The proposed work analyses the performance of the KNN, SVM and Neural network classifiers and also analyses the mobile users’ affinity and usage nature based on different age groups.

Keywords

K nearest neighbour Neural network SVM Mobile dataset 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceSri. S. Ramasamy Naidu Memorial CollegeSatturIndia

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