Presently, in the research processes involved in analysing the relationship between smoking and vital capacity, most researchers use statistical software to analyse, count the differences of vital capacity between different groups and carry out linear analysis or regression analysis. They cannot deeply analyse the relationship between the data, nor can they get the correlation of the data itself. Considering these limitations, this paper studies the influence of adolescent smoking on physical training vital capacity in eastern coastal areas. Based on the brief introduction of the research progress of data mining algorithm, and taking the teenagers in the eastern coastal area as the research object, the k-means algorithm and decision tree algorithm are applied to the data mining of vital capacity of physical training, after which we classify and reclassify the data, mine the rules between the data and put forward improvement strategies for the shortcomings of the algorithm itself. Finally, experiments are designed to analyse the accuracy, running time and reliability of the algorithm. The experimental results show that the improved k-means algorithm and decision tree algorithm shorten the running time and enhance the stability, and can realise the classification and mining of vital capacity data of physical training, so as to improve the reliability of experimental result analysis.