Resumen
The article focuses on the field of data mining, which addresses the question of how best to use historical data to discover general regularities and improve the process of making decisions. The increasing interest in data mining, or the use of historical data to discover regularities and improve future decisions, follows from the confluence of several recent trends that is, the falling cost of large data storage devices and the increasing ease of collecting data over networks, the development of robust and efficient machine learning algorithms to process this data and the falling cost of computational power enabling use of computationally intensive methods for data analysis. The field of data mining, sometimes called knowledge discovery from databases or advanced data analysis and machine learning, has already produced practical applications in such areas as analyzing medical outcomes, detecting credit card fraud, predicting customer purchase behavior, predicting the personal interests of Web users, and optimizing manufacturing processes. It has also led to a set of fascinating scientific questions