Application of Data Mining Technology in Music Education Information

This paper also evaluates various classification algorithm models and determines that the K nearest neighbor prediction model has the best performance in classifying and predicting academic performance; Based on the research results, suggestions for timely teaching interventions in the online learning process are provided, with a view to providing useful references for teachers to understand the learning situation of online learners, learners to improve the effectiveness of online learning, and managers to optimize educational decision-making. Music education is a research field that has existed for many years. It is an art form passed down from generation to generation, which can be said to be one of the most important things in life. Music plays a very important role in our life. It can bring out the best or worst emotions in our hearts. It is also considered one of the most popular forms of entertainment in the world. In this era, technology is very important in almost every aspect of life. With the progress of technology, new methods are needed to use it to make things easier or more efficient. One area where technology can be used to make things easier or more effective is music education. The main idea of the content-based method is that a document can be described by a set of features directly calculated from its content. Generally speaking, content-based multimedia data access requires specific methods, which must be customized for each specific media. However, the core information retrieval (IR) technology based on statistics and probability theory can be more widely used outside the text, because the underlying model can describe the basic features shared by different media, languages and application fields.