Research on Classification Model of Equipment Support Personnel Based on Collaborative Filtering and Xgboost Algorithm

With the intensity of war, the improvement of the complexity of information technology and equipment, the demand for equipment support personnel is getting higher and higher, and the professional division of labor needs more and more clear, but the professional knowledge and maintenance ability of each equipment security personnel have a greater difference. The task is more and more sophisticated, but the equipment security personnel is limited, which made a new demand of equipment support personnel in accordance with the ability to classify and match the staff, ability and task automatically. From the point of view of data mining, we find the relationship between data and ability, task and ability, and provide accurate and convenient personnel classification method for the future combat. According to the method of capability classification, we use collaborative filtering and xgboost algorithm to carry on the classification model of equipment support personnel. The results show that the error of classification decreases with the increase of data volume. At present, when we collect more than 300 samples, the error is 0.04.