针对有少量野点出现的情况,提出一种基于马氏椭球学习机的监督野点探测(supervised outlier detection based on Mahalanobis ellipsoidal learning machine,SODMELM)方法。这种方法通过一个超椭球对正常类进行较好的描述的同时,将野点...针对有少量野点出现的情况,提出一种基于马氏椭球学习机的监督野点探测(supervised outlier detection based on Mahalanobis ellipsoidal learning machine,SODMELM)方法。这种方法通过一个超椭球对正常类进行较好的描述的同时,将野点排除在该椭球外面,继承了马氏椭球学习机(Mahalanobis Ellipsoidal Learning Machine,MELM)将样本点的协方差矩阵即样本点的分布信息考虑进去的优点。真实数据上的实验表明了所提的方法在一般意义上能提高野点探测的效率。展开更多
The paper introduces the approach of outher detection based on kernel,and points out the approach is hard to be realized with the increase of sample number. In order to reduce the size of optimization,the sample selec...The paper introduces the approach of outher detection based on kernel,and points out the approach is hard to be realized with the increase of sample number. In order to reduce the size of optimization,the sample selection method based on distance is proposed Through selecting samples,the computation workload and the demand of EMS memory can be decreased greatly. In the end,the real-time demand can be met.展开更多
文摘The paper introduces the approach of outher detection based on kernel,and points out the approach is hard to be realized with the increase of sample number. In order to reduce the size of optimization,the sample selection method based on distance is proposed Through selecting samples,the computation workload and the demand of EMS memory can be decreased greatly. In the end,the real-time demand can be met.
