Toward Labor Legal Risk Assessment Based on Unbiased Iterative Brunching Decision Tree Algorithm

Abstract

In recent years, with the advancement of China’s labor laws and regulations, especially the strengthening of workers’ awareness of legal rights protection, enterprise labor risk is rising. It is essential for trade unions to help enterprises establish and improve the risk assessment mechanism of labor and employment on time, work hard from the four links of prediction, preexamination, forecast, and prevention urge enterprises to employ workers under the law, effectively reduce labor disputes, avoid the rise of conflicts, and maintain the stability of enterprises and society. In the background of building a harmonious society, the employment of enterprises has been paid more attention by the government, industry, and schools. Particularly for enterprises, market competition largely comes down to talent competition. In the global talent shortage, legal employment and risk prevention have been placed in front of enterprises. This is especially true for state-owned enterprises. More, under the prevailing situation of protecting workers’ rights, interests, and increasing legal awareness of enterprises and workers, it is more prominent for state-owned enterprises to carry the mission and responsibility of building a harmonious society. Its employment plays a leading role in the whole society or industry. The pragmatic purpose of this work is to deal with the risk management-related theory to the study of legal risk prevention and control of employment using the method of risk identification related to the current domestic and foreign through decision tree algorithm (DTA) about the ocean enterprise employee to assess international agreements and legal rules. Given the ocean enterprise employee specifically the seafarers’ employment combined with industry norms, the ideas, and measures of legitimate employment, this study has a strong theoretical and practical guiding importance for practical work.