Simulation analysis for the financial development of real estate using an improved machine learning algorithm

To improve the accuracy of analyzing the development of real estate finance, this article has made specific improvements to traditional machine learning algorithms. The improvement method mainly applies the generalized linear model to conduct in-depth analysis and exploration of the development effect of real estate finance, and comprehensively uses the liquid type logarithmic linear model and the overall logarithmic linear model. These models are used to evaluate the impact of various combinations of real estate finance development methods on the effectiveness of incoming calls and visits, in order to recommend relatively better types of real estate finance development. By analyzing the model, this article can preliminarily simulate the investment standards for future real estate finance development and evaluate their development effects in advance. Compared with traditional real estate financial analysis methods, the method proposed in this paper demonstrates significant advantages in prediction accuracy and application scope. Based on experimental simulation research, it is known that the simulation method for the development of real estate finance based on improved machine learning algorithms has good results and provides strong support for decision-making in the field of real estate finance.