Method for training endometriosis cyst rupture data based on random forest algorithm

The invention provides a method for training endometriosis cyst rupture data based on a random forest algorithm, and the method comprises the steps: obtaining endometriosis cyst rupture and non-rupture data as sample data, carrying out the normalization processing, and dividing the sample data into a test set and a plurality of training sets; performing decision tree training on each training setto obtain a corresponding CART decision tree model; selecting an optimal feature from each CART decision tree model through Gini index comparison to perform branching processing to obtain a corresponding decision tree and form a random forest model; performing parameter optimization on the random forest model by adopting a particle swarm algorithm, and importing the random forest model into the training set and the test set to obtain a trained random forest model; and acquiring endometriosis cyst data to be detected, importing the data into the trained random forest model, and distinguishing rupture or non-rupture dat