A Novel Ensemble Technique for the Prediction of Heart Disease Using Feature Selection Methods

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Data mining is the process of analysing large sets of data in order to discover meaningful patterns and relationships. It involves using a combination of statistical analysis, machine learning algorithms, and data visualization techniques to uncover hidden insights that can inform business decisions or provide new insights into a particular field. One of the key benefits of data mining is its ability to extract valuable insights from vast amounts of data that might be difficult or impossible to analyse manually. For example, data mining can help businesses understand customer behaviour and preferences, identify potential risks or opportunities, and improve operational efficiency. Data mining is used in a variety of fields, including finance, healthcare, marketing, and science. It can be used to detect fraud in financial transactions, predict disease outbreaks in healthcare, target marketing campaigns more effectively, and identify new scientific discoveries. However, data mining also raises important ethical and privacy concerns. The use of personal data without individuals' consent or knowledge can lead to potential violations of privacy and discrimination. Therefore, it is essential to use data mining in a responsible and ethical manner, while maintaining transparency and accountability.