Recognition of Building Health Status Based on Machine Learning Algorithm

In order to improve the results of building health status recognition, a method of building health status detection based on machine learning algorithms is proposed. First analyze the process of building health status recognition, find the factors that affect the building health status recognition effect, and then select the main influencing factors for building health status recognition modeling, and introduce machine learning algorithms to describe the building health status and influencing factors The internal connection between the building health status recognition model is established, and finally the effectiveness and superiority of the method are analyzed using specific building health status recognition examples. The average recognition rate of the building health status exceeds 92% while the current classic The method's recognition rate of building health status does not exceed 90%, and the recognition speed is faster, which has better practical application value.