INVESTIGATING DATA MINING METHODS FOR PATTERN AND RELATIONSHIP DETECTION IN LARGE DATASETS
Keywords:
Data Mining, Pattern Detection, Relationship Detection, Clustering, Neural Networks, Large Datasets, Association Rule Mining, Predictive Analytics, Comparative Analysis, Big DataAbstract
Data mining methods play a crucial role in uncovering hidden patterns and relationships in large datasets, providing valuable insights for decision-making and predictive analytics. This paper investigates various data mining techniques such as association rule mining, clustering, and neural networks, with a focus on their ability to detect patterns and relationships in large-scale data. A comparative analysis of these methods is presented, evaluating their performance on different types of data and metrics such as accuracy, precision, and computational efficiency. The results highlight the strengths and limitations of each method, suggesting areas for future improvement in the application of data mining for complex datasets.
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Copyright (c) 2023 Salumanda, Christian (Author)
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