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Futuristic Prediction of Missing Value Imputation Methods Using Extended ANN

Author

Listed:
  • Ashok Kumar Tripathi

    (Jaypee University of Information Technology, India)

  • Hemraj Saini

    (Jaypee University of Information and Technology, India)

  • Geetanjali Rathee

    (Netaji Subhas University of Technology, India)

Abstract

Missing data is universal complexity for most part of the research fields which introduces the part of uncertainty into data analysis. We can take place due to many types of motives such as samples mishandling, unable to collect an observation, measurement errors, aberrant value deleted, or merely be short of study. The nourishment area is not an exemption to the difficulty of data missing. Most frequently, this difficulty is determined by manipulative means or medians from the existing datasets which need improvements. The paper proposed hybrid schemes of MICE and ANN known as extended ANN to search and analyze the missing values and perform imputations in the given dataset. The proposed mechanism is efficiently able to analyze the blank entries and fill them with proper examining their neighboring records in order to improve the accuracy of the dataset. In order to validate the proposed scheme, the extended ANN is further compared against various recent algorithms or mechanisms to analyze the efficiency as well as the accuracy of the results.

Suggested Citation

  • Ashok Kumar Tripathi & Hemraj Saini & Geetanjali Rathee, 2022. "Futuristic Prediction of Missing Value Imputation Methods Using Extended ANN," International Journal of Business Analytics (IJBAN), IGI Global, vol. 9(3), pages 1-12, July.
    • Handle: RePEc:igg:jban00:v:9:y:2022:i:3:p:1-12
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    1. Alexey Valentinovich Bogoviz & Svetlana Vladislavlevna Lobova & Yulia Vyacheslavovna Ragulina & Alexander Nikolaevich Alekseev, 2018. "A Critical Review of Russia s Energy Efficiency Policies in Agriculture," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 67-75.
    2. Xiaogeng Ren & Chunwang Li & Xiaojun Ma & Fuxiang Chen & Haoyu Wang & Ashutosh Sharma & Gurjot Singh Gaba & Mehedi Masud, 2021. "Design of Multi-Information Fusion Based Intelligent Electrical Fire Detection System for Green Buildings," Sustainability, MDPI, vol. 13(6), pages 1-15, March.
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    1. Che-Yu Hung & Chien-Chih Wang & Shi-Woei Lin & Bernard C. Jiang, 2022. "An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data," Sustainability, MDPI, vol. 14(4), pages 1-21, February.

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