Application research of improved K-means leave one out method in rejecting of abnormal samples of coal near infrared spectrum

In view of problems of time-consuming, misjudgment of rejecting abnormal sample existed in current leave one out method, an improved K-means leave one out method was put forward for detecting and eliminating abnormal sample in coal quality analysis. Firstly, the method uses K-means clustering method to cluster samples, and gets suspicious samples; then it takes suspicious samples as a validation set, adopts leave one out method to do quadratic distinguishing, so as to eliminate abnormal samples. The experimental results show that the K-means leave one out method can eliminate abnormal samples quickly and accurately, and improves prediction accuracy of models.