The invention discloses a network business flow feature selecting and classifying method based on a multi-objective adaptive evolutionary algorithm, comprising the following steps of: firstly sortingthe features by using an information gain ratio and filtering part of irrelevant features to rapidly reduce dimension, then searching a feature space according to the adaptive evolutionary algorithm,using the feature having the top-raking information gain ratio as an initial population, and regarding two target functions of an inconsistent rate and a feature subset dimension as evaluation functions for selecting an optimal feature subset. Adaptive crossover and mutation maintain the population diversity, and the convergence ability of the algorithm is ensured. At the same time, by using a designed three-layer KNN classifier model, the invention classifies six multimedia business flows of online standard-definition live video, web browsing (Baidu), online audio, web browsing (sina), network voice chat and online standard-definition non-live video. The experiment result shows that the invention has higher classification accuracy compared to existing method.