Application Analysis of Probability Theory and Mathematical Statistics in Data Mining
Download as PDF
Data mining refers to the process of applying data analysis and data discovery algorithms to obtain potentially available patterns or guiding rules from a database. With the development of computer and network technology, there are a large number of large and wide-ranging data. It is impossible to analyze such data by the traditional statistical method of simple summary and analysis according to the specified mode. Probability theory and mathematical statistics are technologies used in data statistics, but they also play a very important role in data mining. Data mining and statistics should learn from and permeate each other, divide their work and work together to contribute to the mining of valuable knowledge hidden behind complex phenomena. Therefore, data mining is a cross-disciplinary subject. It promotes people's application of data from low-level simple query to mining knowledge from data to provide decision support. This paper briefly analyzes the application of probability theory and mathematical statistics in data mining.
Data mining, Probability theory, Mathematical statistics, Statistics, Application