Female Employment Data Analysis Based on Decision Tree Algorithm and Association Rule Analysis Method

Improving the employment rate and quality of women’s employment has been a hot spot of social concern in recent years. Traditional female employment information has not been fully utilized; only simple storage and query functions have been completed. In order to mine and use female employment information, we find the rules that exist in it, and to better understand the current female employment problems, this article focuses on the data mining of female employment information data. This paper introduces in detail the current employment trends of women and the advantages of decision tree algorithms, the hot content and key technical points of data mining technology, the research progress of this technology at home and abroad, etc. Decision tree analysis algorithm for association rules: According to the formula calculus, the advantages of the decision tree algorithm and the association rule analysis method are displayed more clearly. The model of female employment information is mainly constructed, and the process of data collection and data model establishment is introduced. According to a set of female employment information data, the algorithm is analyzed through the decision tree analysis algorithm based on association rules, and the reliability of the algorithm is verified. Finally, the whole article is summarized, and its basic contents are explained. The decision tree analysis method based on association rules can effectively dig out the information hidden in the female employment information data, and it has an important role in guiding the self planning of college women. This algorithm has the characteristics of high operating efficiency and stable results, and it also has a positive effect on other types of data mining.