Data Association Mining Method of Vocational College Students’ Employment Education Based on Machine Learning Model

In the process of data association mining using traditional methods, data mining is affected by incomplete data mining, resulting in large errors in data mining. A data association mining method based on machine learning model for vocational college students’ employment education is proposed. Analyze the internal and external factors affecting students’ employment, calculate the difference series formed by two data under a certain time series, and determine the spatial correlation of the series. The confidence is compared with the expected confidence, and the interest is obtained. According to the association rules, the machine learning model of educational data association rules is constructed. Build a data gain evaluation function, calculate the frequency of word segmentation feature set in education data, and calculate the similarity between any two education data. Through the similarity calculation results of association oriented data, the implicit low rank characteristics of the data are obtained, and the association education data clustering is realized. Preprocess the associated data, and design the process of clustering data association mining under the machine learning model. The experimental results show that the mining data type of this method is consistent with the experimental data type, and the minimum mining error is 0.05, which shows that this method can obtain good mining results.