Probabilistic and . . . Interval . . . Why Not Maximum . . . Chip Design: Case . . . General Approach: . . . Interval Approach: . . . Extension of Interval . . . Successes (cont-d) Challenges Problem Main Idea: Use Moments Formulation of the . . . Result Case Study: . . . General Problem Case Study: Detecting . . . Outlier Detection . . . Outlier Detection . . . Fuzzy Uncertainty: In . . . Ackn...

Outlier detection is an important task in data mining and its applications. It is defined as a data point which is very much different from the rest of the data based on some measures. Such a data often contains useful information on abnormal behavior of the system described by patterns. In this paper, a novel method for outlier detection is proposed among inconsistent dataset. This method expl...

Outlier detection is one of the obstacles of big dataset analysis because of its time consumption issues. This paper proposes a fast outlier detection method for big datasets, which is a combination of cell-based algorithms and a ranking-based algorithm with various depths. A cell-based algorithm is proposed to transform a very large dataset to a fairly small set of weighted cells based on pred...

Detecting outliers which are grossly different from or inconsistent with the remaining spatio-temporal dataset is a major challenge in real-world knowledge discovery and data mining applications. In this paper, we deal with the outlier detection problem in spatio-temporal data and we describe a rough set approach that finds the top outliers in an unlabeled spatio-temporal dataset. The proposed ...

It is important to preprocess high-throughput data generated from microarray or mass spectrometry experiments in order to obtain a successful analysis. Outlier detection is an important preprocessing step. For outlier detection, upper and lower fences (Q3+1.5IQR and Q1 − 1.5IQR) of the differences are often used in statistics, where Q1=lower 25% quantile, Q3=upper 25% quantile, and IQR = Q3 − Q...

In this article, a new outlier-resistant mechanism is proposed to deal with the variance-constrained filtering problem for class of networked systems subject sensor resolution under round-robin protocol (RRP). Sensor resolution, which serves as an important index in determining measurement accuracy, taken into account addressed problem, and sensor-resolution-induced uncertainty tackled by using...

estimation of gold reserves and resources has been of interest to mining engineers and geologists for ages. the existence of outlier values shows the economic part of the deposits subject to the fact that don’t depend on the human or technical errors. the presence of these high values causes a pseudo dramatically increment in variance estimation of economical blocks when applying conventional m...

Estimation of gold reserves and resources has been of interest to mining engineers and geologists for ages. The existence of outlier values shows the economic part of the deposits subject to the fact that don’t depend on the human or technical errors. The presence of these high values causes a pseudo dramatically increment in variance estimation of economical blocks when applying conventional m...