Читать книгу Handbook on Intelligent Healthcare Analytics - Группа авторов - Страница 41

Statistical methods are being used for extraction of hidden structure from the unlabeled data in unsupervised models. Human input is also absent here, and they are utilized in detection of abnormal data along with reduction of dimension of the data. Its applications include clustering as well problems such as data aggregation. The unlabeled data can be partitioned as several groups depending on the similarity feature. This recognition of patterns can be done using the clustering algorithms. On the other hand, the algorithms employed for reduction of dimension like PCA (Principal Component Analysis) play a significant role in data complexity reduction, which, in turn, helps in avoiding overfitting [18].