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A Comprehensive Study of Cryptocurrency Trend Analysis Based on a Novel Machine Learning Technique

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Cryptology and Network Security with Machine Learning (ICCNSML 2022)

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Cryptocurrencies are digital blockchain technology-based money that mainly got into the trend in 2015. In the present manuscript, we are finding a Machine Learning-based technique that would be best optimized to predict the prices of cryptocurrencies. We have applied Linear Regression and Bayesian models on five cryptocurrency datasets gathered from Kaggle. First, the datasets are split into testing and training data and then the model is run over all the cryptocurrency datasets. Training of every model on the training dataset is done and later it is tested and individually analyzed by checking its precision and accuracy. We then tried to obtain a comparative analysis of the models. Then we have created a tabular representation of the comparative analysis so that it can be used to determine which model is working best.

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References

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Acknowledgements

We are very much thankful to the anonymous reviewers for suggesting the points/mistakes which have been well implemented/corrected for the necessary improvement of the manuscript. We sincerely acknowledge our deep sense of gratitude to the Editorial office and reviewers for giving their valuable time to the manuscript.

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Authors and Affiliations

  1. Jaypee University of Information Technology, Waknaghat Solan, 173 234, Himachal Pradesh, India

    Paras Sharma, Adhiraj Gupta, Rakesh Kumar Bajaj & Prateek Thakral

Authors
  1. Paras Sharma
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  2. Adhiraj Gupta
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  3. Rakesh Kumar Bajaj
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  4. Prateek Thakral
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Corresponding author

Correspondence to Rakesh Kumar Bajaj .

Editor information

Editors and Affiliations

  1. Applied Statistics Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Bimal Kumar Roy

  2. Department of Mathematics, Pranveer Singh Institute of Technology, Kanpur, India

    Atul Chaturvedi

  3. Department of Mathematics, Bar-Ilan University, Ramat Gan, Israel

    Boaz Tsaban

  4. Department of Mathematics, Indian Institute of Technology Jammu, Jammu, Jammu and Kashmir, India

    Sartaj Ul Hasan

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sharma, P., Gupta, A., Kumar Bajaj, R., Thakral, P. (2024). A Comprehensive Study of Cryptocurrency Trend Analysis Based on a Novel Machine Learning Technique. In: Roy, B.K., Chaturvedi, A., Tsaban, B., Hasan, S.U. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2022. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-2229-1_5

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  • DOI: https://doi.org/10.1007/978-981-99-2229-1_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2228-4

  • Online ISBN: 978-981-99-2229-1

  • eBook Packages: EngineeringEngineering (R0)

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