Pattern Based Outlier in Mixed Attribute Data
Towards Outlier Detection For Scattered Data and Mixed Attribute Data
... the mixed attribute problem, traditional outlier detection meth- ods often fail to effectively identify outliers, due to the lack of the mechanisms to consider the interactions among various types of ...
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An Outlier Mining Algorithm Based on Attribute Entropy
... the outlier data mining and commonly used outlier mining methods, on this basis, it proposes an outlier mining algorithm based on attribute entropy ...of attribute entropy ...
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A Semi-Supervised Feature Engineering Method for Effective Outlier Detection in Mixed Attribute Data Sets
... 13 Another widely used density-based algorithm is DBSCAN initially developed to cluster spatial systems with unrestricted cluster shapes [14]. DBSCAN algorithm takes into consideration the minimum number of points ...
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WMFP-Outlier: An Efficient Maximal Frequent-Pattern-Based Outlier Detection Approach for Weighted Data Streams
... of outlier detection via the FindFPOF method, an improved frequent- pattern-based outlier detection approach, name- ly, LFP [17], was proposed, which used the ratio of the longest length among ...
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Outlier Detection for Mixed Model with Application to RNA-Seq Data
... still based on the Poly(A) RNA-Seq measurements, and it is costly to reproduce the reference libraries for Capture RNA-Seq ...of data without ...the data by using the mixed model rewards ...
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An Efficient Outlier Detection Using Amalgamation of Clustering and Attribute-Entropy Based Approach
... continuous data streams brings unique opportunities but also new ...Thus data stream has become a dynamic research area of Data ...mining. Data Stream Mining is the process of extracting ...
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An Efficient Technique for Clustering Data with Mixed Attribute Types
... categorical attribute that represents the eye colors. Based on Equation (1), the distance between the brown and hazel is one and that between brown and blue is one as well, however, the colors brown and ...
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Correspondence Pattern Attribute Selection for Consumption of Federated Data Sources
... consuming data from federated domains, it is often necessary to identify the relationships that exist between the data schemas used in each ...to data set schema ...the attribute values of a ...
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Post Mining based Pattern Filtering Scheme with Attribute Association
... of data in the data warehouse, searching for frequently recurring patterns, detecting trends and unearthing ...of data warehouse or data mart data are inspected and facts/knowledge ...
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Average Weight based Pattern Frequency for Performing Outlier Mining in Web Documents
... Also, search engine extracts tens and hundreds of web pages by comparing the terms of a single user query. They undergo millions of queries as a request from web users at each and every hour. Besides, due to ...
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Cluster Based Outlier Detection Algorithm for Healthcare Data
... Big Data, High dimensional data, Uncertain data, Time Series data, Biological data, ...the data may be erroneous, missing or not ...of data preprocessing for ...
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Model-based Outlier Detection for Object-Relational Data
... Metric-based Outlier Detection In chapter 4 we introduced a pipeline propositionalization method to convert object-relational data to a single data ...relational data in one data ...
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A Comparison among Data Mining Algorithms for Outlier Detection using Flow Pattern Experiments
... on data sets, compared to other methods, the Reynolds shear stress parameter signicantly decreased by about ...Overall, based on Table 12, it can be stated that in the case of the bend without a spur dike, ...
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Scalable And Efficient Outlier Detection In Large Distributed Data Sets With Mixed-type Attributes
... dissertation, outlier Detection has attracted substantial atten- tion in many applications and research areas; some of the most prominent applications are network intrusion detection or credit card fraud ...are ...
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Outlier detection in multivariate functional data based on a geometric aggregation
... of mixed type. However, it is hard to interpret what such mixed type outliers are made up: given a detected outlier, ideally one would like to access to the amount of the different outlyingness ...
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A Distribution based Approach of Outlier Removal for Software Effort Data
... Further evidence of uncertainty in software effort estimation is the attribute instability problem identified by Menzies et al. [15] regarding Boehm‟s delta estimation method. The delta estimation method proposed ...
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ABSTRACT : Outlier detection is the process of finding outlying pattern from a given dataset. Outlier detection
... k-occurrences based on given similarity or distance measure as Nk(x),that the number of times x occurs among all other points in k nearest neighbor and points those frequently occurred as a hubs and points those ...
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Key Escrowing Problem and Attribute Based Data Access
... ideal pattern for client which gives numerous advantageous ...property based get to control instruments utilized as a part of existing ...trait based encryption plans, for example, ...
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A web-based interactive data visualization system for outlier subspace analysis
... The data to be displayed can include both the original high-dimensional data set and the outlier detection results after data pre-processing which includes standard steps of data ...
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Data-driven pattern identification and outlier detection in time series
... of data-driven pattern identification and outlier detection in time ...a data mining perspective, this opens up new ways of analyzing time series in a data-driven, bottom-up ...
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