Enterprise AI Analysis

Numerous studies have shown that economic contribution and division of housework are the two central factors influencing marital satisfaction. Economic contribution affects marital quality mainly through the channels of economic security, decision-making power and quality of life, while housework involves aspects of marital justice, sharing of responsibilities and emotional attachment. Research suggests that the distribution of household economic resources not only affects the material standard of living of both spouses, but may also influence the power structure of the relationship, which in turn affects marital stability and satisfaction. In some socio-cultural contexts, the party with the higher economic contribution tends to have a greater say in household decisions, while the party with the lower economic contribution may feel a degree of financial depen-dence, which may reduce their marital satisfaction. However, it is not enough to look at the absolute value of an individual's financial contribution. Studies have found that the balance of contributions between couples is more important than the absolute amount of contributions. This means that if the imbalance between financial and domestic contributions is too great, it may lead to a sense of unfairness in the marriage, which may reduce marital satisfaction.

XGBoost (Extreme Gradient Boosting) is an optimization algorithm based on Gradient Boosting Decision Trees (GBDT). It gradually optimizes the prediction results and improves the generalization ability of the model by constructing multiple weighted decision trees. Its core idea is to gradually build multiple decision trees through the additive model, and each tree is used to correct the prediction error of the previous tree. The objective function consists of two parts: loss function and regularization term, used to measure deviation and prevent overfitting. XGBoost optimizes the model through the gradient boosting method, updating the predicted value at each step.