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Computer Science > Machine Learning

arXiv:2406.03507 (cs)
[Submitted on 5 Jun 2024]

Title:Robust Prediction Model for Multidimensional and Unbalanced Datasets

Authors:Pooja Thakar, Anil Mehta, Manisha
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Abstract:Data Mining is a promising field and is applied in multiple domains for its predictive capabilities. Data in the real world cannot be readily used for data mining as it suffers from the problems of multidimensionality, unbalance and missing values. It is difficult to use its predictive capabilities by novice users. It is difficult for a beginner to find the relevant set of attributes from a large pool of data available. The paper presents a Robust Prediction Model that finds a relevant set of attributes; resolves the problems of unbalanced and multidimensional real-life datasets and helps in finding patterns for informed decision making. Model is tested upon five different datasets in the domain of Health Sector, Education, Business and Fraud Detection. The results showcase the robust behaviour of the model and its applicability in various domains.
Comments: 9 pages
Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)
Cite as: arXiv:2406.03507 [cs.LG]
  (or arXiv:2406.03507v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2406.03507

Submission history

From: Pooja Thakar [view email]
[v1] Wed, 5 Jun 2024 06:28:39 UTC (342 KB)
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