On Line Teaching Data Classification Method for Ramp Control Specialty in Universities Based on Machine Learning Model

In order to improve the accuracy of online teaching data classification results and provide comprehensive technical guidance and help for the standardized implementation of quality education, the machine learning model was introduced to carry out the design and research of online teaching data classification methods, taking the apron control specialty of a university as an example. Collect the basic information of college students majoring in apron control, the information generated in the teaching process, and the phased achievements of professional online teaching, build the online teaching database of college students majoring in apron control, and preprocess the data according to the specifications; The machine learning model is innovatively introduced to visually process the data. The encoding tool is used to transform the data format, so as to achieve the extraction of data characteristics; Calculate the similarity of the online teaching data characteristics of the apron control specialty in colleges and universities, set the classification criteria for the online teaching data of the apron control specialty in colleges and universities, and when the data similarity exceeds the set criteria, divide the data into the same category to complete the design of the classification method. The experimental results show that the designed classification method has a good application effect, and this method can effectively improve the accuracy of the classification results.