The invention discloses a
cervical cancer prediction method based on adaptive KNN
noise recognition, and the method comprises the steps: firstly obtaining a
cervical cancer data set, carrying out the missing value
processing, newly building target features, and carrying out the feature
correlation analysis and
standardization processing; performing mark classification on data in the standardized
cervical cancer data set by using
noise identification based on adaptive KNN, and performing
oversampling by using a category-based mixed sampling
algorithm; and finally performing classification training and predicting a
test set to obtain a prediction result. According to the method, the K value is adaptively determined through
kernel density estimation, recognition is carried out through neighborhood information in the
noise recognition process, noise recognition is carried out through adjacent sample information of a certain sample, noise data can be more effectively recognized, meanwhile, the data can be reasonably divided, and when balance data is calculated through
oversampling, the noise data can be more effectively recognized. New noise generated in
synthetic data is reduced, and the method has high prediction precision in cervical
cancer prediction, so that the death rate of women caused by cervical
cancer is reduced.