AN INSIGHT THROUGH REVIEWS ON NEURAL NETWORK-BASED DATA MINING

Companies have been gathering data for decades and storing it in vast data centres. Despite the fact that this data is readily accessible, only a few organisations have been willing to understand the true meaning contained inside it. How to generate this value is the dilemma these businesses are pondering. Data mining is the solution. Artificial Neural Networks, Regression, and Decision Trees are only a few of the tools open to data miners. Because of their black box existence, many practitioners are suspicious of Neural Networks topology, despite their success in a variety of contexts. This paper provides an analysis of artificial neural networks and challenges their popularity as a data mining method. Neural networks provide a broad range of applications in data mining. Despite their complicated nature, long training period, and difficult-tounderstand results representation, neural networks have a strong acceptance capacity for noisy data and high precision, making them preferable in data mining. In this article, the main technologies and methods for achieving data mining based on neural networks are investigated in depth, as well as the key technology and methods for achieving data mining based on neural networks.