We establish the relevant mathematical model based on the distance-based outlier detection method (DBODM) to analysis the gateway. When the deviation value is more than a certain threshold, the redundant node changes the nodes' working patterns through sending the intelligent decision message, to ...
Outlier detection is considered an important data mining task, aiming at the discovery of elements (also known as outliers) that show significant diversion from the expected case. Most of the existing methods are based on distance measure. But in case of data stream these method is not efficient...
maximal data piling distancemultiple outliersDespite the popularity of high dimension, low sample size data analysis, there has not been enough attention to the sample integrity issue, in particular, a possibility of outliers in the data. A new outlier detection procedure for data with much larger...
Detecting outliers in data is an important problem with interesting applications in a myriad of domains ranging from data cleaning to financial fraud detection and from network intrusion detection to clinical diagnosis of diseases. Over the last decade of research, distance-based outlier detection algori...
Kitagawa, Distance-based outlier detection on uncertain data of gaussian distribution, in: APWeb, Lecture Notes in Computer Science, vol. 7235, Springer, 2012, pp. 109-121.Shaikh, S.A., Kitagawa, H.: Distance-based outlier detection on uncertain data of Gaussian distribution. In: APWeb, ...
2. 2018-02 EFFICIENT GAN-BASED ANOMALY DETECTION 针对AnoGAN测试阶段仍然需要更新参数的缺陷,此方法提出一种基于BiGAN可快百倍的方法。 训练时,同时学习将输入样本x映射到潜在表示z的编码器E,以及生成器G和判别器D: 如此可避免测试仍需要“找到z”那个耗时的步骤。与常规GAN中的D仅考虑输入(实际的或生成的)图...
Fast Top-k Distance-Based Outlier Detection on Uncertain Data This paper studies the problem of top- k distance-based outlier detection on uncertain data. In this work, an uncertain object is modelled by a probabilit... SA Shaikh,H Kitagawa - Springer, Berlin, Heidelberg 被引量: 48发表: ...
Local Outlier Factor method is discussedhereusing density based methods. Distance based approaches will have problem finding an outlier like point O2. Because the points in cluster C1 are less dense compare to cluster C2. If we chose a large threshold to capture an outlier like O2, many of th...
Outlier detection using statistics provides a simple framework for building a distribution model and for detection based on the variance of the data point from the mean. From: Data Science (Second Edition), 2019 About this pageSet alert Also in subject areas: Computer Science EngineeringDiscover ot...
S. A. Shaikh and H. Kitagawa, "Fast top-k distance-based outlier detection on uncertain data," in WAIM, 2013.Shaikh, S.A., Kitagawa, H.: Fast top- k distance-based outlier detection on uncertain data. In: Wang, J., Xiong, H., Ishikawa, Y., Xu, J., Zhou, J. (eds.) WAIM...