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Ikvinderpal Singh, Sapandeep Kaur Dhillon
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- Assistant Professor, Assistant Professor, Department of Computer Science & Applications, TSGGS Khalsa College, Amritsar., Department of Computer Science, Guru Nanak Dev University, Amritsar., Punjab, Punjab, India, India
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Abstract
nIn the realm of machine learning, data structures play a pivotal role in facilitating efficient data manipulation, storage, and retrieval, thereby significantly impacting the performance and scalability of machine learning algorithms. In recent years, the field of machine learning has witnessed the emergence of novel data structures tailored to address scalability and efficiency challenges inherent in handling large-scale and high-dimensional data. This paper provides a look at the data preprocessing, data cleaning and feature extraction in machine learning using data structures. This paper explores three key emerging trends: tensor representations, sparse data structures, and graph-based neural networks, highlighting their potential to revolutionize modern machine learning applications. Furthermore, we discusseda case study of the Leveraging Emerging Data Structures in Healthcare Analytics.
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Keywords: Machine Learning, Data Structures, Tensor Representations, Sparse Data Structures, Graph-Based Neural Networks
n[if 424 equals=”Regular Issue”][This article belongs to International Journal of Data Structure Studies(ijdss)]
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References
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| Volume | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | |
| Received | February 16, 2024 |
| Accepted | February 19, 2024 |
| Published |
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