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Data Analytics Implemented over E-commerce Data to Evaluate Performance of Supervised Learning Approaches in Relation to Customer Behavior

  • Kailash HambardeEmail author
  • Gökhan Silahtaroğlu
  • Santosh Khamitkar
  • Parag Bhalchandra
  • Husen Shaikh
  • Govind Kulkarni
  • Pritam Tamsekar
  • Pranita Samale
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1048)

Abstract

Online purchase portals have a spectacular opportunity for business expansion. E-commerce portals have data repositories pertaining to online transactions that could be analyzed through data analytics to find valuable insight for further expansion of business as well as targeted marketing. This study has made an attempt for the implementation of data analytics over the shared data set of Turkey-based e-commerce company. Precisely, a comparative analysis of supervised machine learning algorithms has been worked out for predicting customer behavior and products being brought. Their efficiency has been found out and they have been ranked purpose wise. The implementations of algorithms are carried out in Python.

Keywords

Customer behavior analytics Classification Random forest 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Kailash Hambarde
    • 1
    Email author
  • Gökhan Silahtaroğlu
    • 2
  • Santosh Khamitkar
    • 1
  • Parag Bhalchandra
    • 1
  • Husen Shaikh
    • 1
  • Govind Kulkarni
    • 1
  • Pritam Tamsekar
    • 1
  • Pranita Samale
    • 1
  1. 1.School of Computational SciencesSRTM University, NandedNandedIndia
  2. 2.School of Business and Management ScienceI.M. UniversityIstanbulTurkey

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