Neighborhood outlier detection

Chen, Yumin; Miao, Duoqian; Zhang, Hongyun

doi:10.1016/j.eswa.2010.06.040

Cited by 108 publications

(40 citation statements)

References 23 publications

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“…Let S j ⊆ L j contain those objects selected from L j ,"Number of rare classes included" denotes the number of objects in S j that are outliers, and "coverage" denotes the ratio of "Number of rare classes included" to |R L j |, 1 ≤ j ≤ 4 [17,22]. In Tables 2-5, "Accuracy" is used to measure the effectiveness of each outlier detection method on the current data set, which is defined as: (9) where N L j denotes the set of all normal objects in L j , and S j denotes the set of all objects selected from L j by the given outlier detection method. From Tables 2-5, it can be seen that for the Lymphography data set, ODGrCR algorithm has the best performance.…”

Section: Lymphography Data Setmentioning

confidence: 99%

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Outlier detection based on granular computing and rough set theory

Jiang

2014

Appl Intell

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In recent years, outlier detection has attracted considerable attention. The identification of outliers is important for many applications, including those related to intrusion detection, credit card fraud, criminal activity in electronic commerce, medical diagnosis and anti-terrorism. Various outlier detection methods have been proposed for solving problems in different domains. In this paper, a new outlier detection method is proposed from the perspectives of granular computing (GrC) and rough set theory. First, we give a definition of outliers called GR(GrC and rough sets)-based outliers. Second, to detect GR-based outliers, an outlier detection algorithm called ODGrCR is proposed. Third, the effectiveness of ODGrCR is evaluated by using a number of real data sets. The experimental results show that our algorithm is effective for outlier detection. In particular, our algorithm takes much less running time than other outlier detection methods.

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Section: Lymphography Data Setmentioning

confidence: 99%

“…Xue and Liu proposed a rough set-based semi-supervised outlier detection method [56]. Chen et al proposed an outlier detection algorithm based on the neighborhood rough set model [9]. Albanese et al extended outlier detection to spatiotemporal data by using a new rough set approach [2].…”

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confidence: 99%

Outlier detection based on granular computing and rough set theory

Jiang

2014

Appl Intell

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“…Hence detection of outliers is very crucial in time series data (Tsay et al, 2000). Several Researchers have recommended detection of outliers as an important aspect of data processing (Chen et al, 2010).…”

Section: Outliers and Detection Of Outliersmentioning

confidence: 99%

An Analysis of the Relationship Between the Sovereign Credit Default Swaps and the Stock Market of Pakistan Through Handling Outliers

Shear¹,

Butt²,

Badshah³

2017

Proceedings of the 8th Economics &Amp; Finance Conference, London

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This study examines the relationship between the Sovereign Credit Default Swap (SCDS) market and Karachi Stock Exchange (KSE). Previous literature in this lieu rarely handles the effect of outliers' presence in data. This study applies Split Sample Skewness Based Boxplot (SSSBB) technique for outlier detection and proposes SSSBB-Winsorization for handling outliers. The results depict a significant role of outliers in the determination of the correlation and causal relationship between these markets. Findings suggest a negative and statistically significant correlation between SCDSand KSE, which is increasing gradually. Moreover, by using Granger causality test, this study finds bidirectional causality between both the markets, which implies informational efficiency of both markets in the prediction of each other.

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“…(5) On the path of the pheromone increment ∆τ ij and Nc cycles were set for the ∆τ ij = 0, Nc = Nc + 1. (6) If Nc Max > Nc, then jump to Step (2). (7) If the condition is satisfied, the current optimal solution will be output.…”

Section: Algorithm Flowmentioning

confidence: 99%

“…How to select the best route of travelling and not miss every scenery has become a problem that needs to be considered. This common example exactly reflects the well-known problems in the field of Mathematics-TSP problem [2], where a businessman visits n cities and then returns back to the starting city, with the premise is that a city can only be visited once to determine the shortest path [3,4].…”

Section: Introductionmentioning

confidence: 99%

An Improved Routing Optimization Algorithm Based on Travelling Salesman Problem for Social Networks

Xiong

2017

Sustainability

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Abstract:A social network is a social structure, which is organized by the relationships or interactions between individuals or groups. Humans link the physical network with social network, and the services in the social world are based on data and analysis, which directly influence decision making in the physical network. In this paper, we focus on a routing optimization algorithm, which solves a well-known and popular problem. Ant colony algorithm is proposed to solve this problem effectively, but random selection strategy of the traditional algorithm causes evolution speed to be slow. Meanwhile, positive feedback and distributed computing model make the algorithm quickly converge. Therefore, how to improve convergence speed and search ability of algorithm is the focus of the current research. The paper proposes the improved scheme. Considering the difficulty about searching for next better city, new parameters are introduced to improve probability of selection, and delay convergence speed of algorithm. To avoid the shortest path being submerged, and improve sensitive speed of finding the shortest path, it updates pheromone regulation formula. The results show that the improved algorithm can effectively improve convergence speed and search ability for achieving higher accuracy and optimal results.

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Neighborhood outlier detection

Cited by 108 publications

References 23 publications

Outlier detection based on granular computing and rough set theory

Outlier detection based on granular computing and rough set theory

An Analysis of the Relationship Between the Sovereign Credit Default Swaps and the Stock Market of Pakistan Through Handling Outliers

An Improved Routing Optimization Algorithm Based on Travelling Salesman Problem for Social Networks

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