1results about How to "Improve classification recognition ability" patented technology

A data re-labeling classification algorithm based on clustering learning comprises the following steps: after preprocessing the expression image data in the original sample, a feature extraction module is used to extract a feature vector to form sample data; a dynamic clustering module splits a sample data set of a minority class into several sub-class data sets, and a sample data set of a majority class remains unchanged; the extracted feature vector is used as the input of the dynamic clustering module; if the sample data belongs to the sample data set of the minority class, the sample data is assigned to the nearest sub-class data set according to the distance between the sample data and the clustering center, and then a pseudo label is assigned to all sample data; the sub-classes are trained by using the pseudo label; and a label mapping module maps the prediction result of the sub-class data set to which the sample data belongs back to the real label space based on the mapping relationship learned in the training process. The application can improve the classification and recognition performance of an unbalanced expression data set, and fully excavates and utilizes the potential information of the sample data set.