[PDF] Top 20 Title: Efficient Classification Technique for Outlier Detection
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Title: Efficient Classification Technique for Outlier Detection
... of outlier is given in ...checked. Outlier detection thus becomes essential in data ...Numerous outlier detection methods have been proposed [3], [4], [5], [9], [10] each with their ... See full document
5
Outlier Detection and Analysis of Data Stream Classification Using Text Clustering
... search title are ...Text classification phase various text clustering methods like c-mean algorithm, Hierarchical agglomerative clustering and single- linkage algorithm are used to classify and clustering ... See full document
5
AN ENHANCED RULE APPROACH FOR NETWORK INTRUSION DETECTION USING EFFICIENT DATA ADAPTED DECISION TREE ALGORITHM
... Intrusion Detection is one of the high priorities & the challenging tasks for network administrators & security ...Intrusion detection system is employed to protect the data integrity, ... See full document
8
A Review on Outlier Detection Techniques
... memory efficient, these techniques preserves the summary of each data stream in terms of candidate outlier and cluster information in memory rather than the complete stream data ... See full document
5
Title: An Efficient Technique for Night Time Vehicle Detection with Fusion Based Image Enhancement
... The enhanced image is obtained using fusion based method. For estimating illumination morphologically closing operation is used. For adjusting illumination a fusion based enhancement algorithm is used. Contrast limited ... See full document
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A SURVEY ON VARIOUS CLASSIFICATION AND NOVEL CLASS DETECTION APPROACHES FOR FEATURE EVOLVING DATA STREAM
... this technique more than one classifier is used for classification with higher ...the classification model is trained on different data ...for classification of dynamic feature data ...model ... See full document
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A TECHNIQUE WITH DIFFERENTIATED SAMPLING IN ANOMALY DETECTION SYSTEM FOR OUTLIER IDENTIFICATION
... anomaly detection problems dealing with large amount of data, adding or removing a target data instance produces only a negligible difference in the resulting eigenvectors and it is not elementary to apply the ... See full document
12
Unsupervised and Semi-supervised Outlier Detection Technique on Distributed Approach
... semi-supervised outlier detection approach for positive and unlabeled data approach to solving the problem where there are few very few positive examples ...neighbor classification use pattern ... See full document
5
Intelligent Anomaly Detection Techniques for Denial of Service Attacks
... clustering-based outlier detection approach achieved 90 percent attack detection rate which seems comparable with other results from literature, whereas false alarm rates as high as 47 percent that ... See full document
12
Enhanced Outlier Detection Method using Association Rule Mining Technique
... of outlier detection, where the aim is to identify data which behave in an unexpected way or have abnormal ...identifies outlier transaction by enhancing an association classification approach ... See full document
6
A Least-squares Approach to Direct Importance Estimation
... and outlier detection, and experimentally confirmed that the proposed uLSIF is computationally more efficient than existing approaches, while the accuracy of uLSIF is comparable to the best existing ... See full document
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AN APPROACH TO DETECT OUTLIERS IN OPENSTREETMAP DATA
... spatial outlier detection, an important branch of spatial data mining, aims to discover those objects whose non-spatial attribute values exhibits different behavior to a great ...spatial outlier ... See full document
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Title: Efficient DDoS Attack Detection and Prevention Framework Using Two-Level Classification in Cloud Environment
... and classification in an efficient way such as machine learning algorithm, supervised and unsupervised ...selection technique was addresed in [5] to select the optimal features from packets by ... See full document
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Title: An Efficient Text Classification Scheme Using Clustering
... in classification process and the results are produced from these techniques is not efficient so system is going to apply the SMTP based similarity measure for better ...is efficient and time saving ... See full document
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AN EFFICIENT ANALYTICS IN CREDIT CARD FRAUD DETECTION USING RESOLUTION CLASSIFICATION (RC) TECHNIQUE
... on Credit Card Fraud Detection Aihua Shen, Rencheng Tong, Yaochen Deng. Abuse is severe issue facing credit-card issuers. Transaction of credit-card is the U.S.A. is 2004 is complete impairment of $800 billion in ... See full document
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Schubert, Erich (2013): Generalized and efficient outlier detection for spatial, temporal, and high-dimensional data mining. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... normalizing outlier scores is motivated by probabilities, the desire for calibrated outlier scores is self-evident, because the concept of calibration has been used to as- sess the reliability of ... See full document
290
A novel symbolization technique for time series outlier detection
... Abstract—The detection of outliers in time series data is a core component of many data-mining applications and broadly applied in industrial ...are efficient in both time and space are ...than ... See full document
9
Efficient Model for Intrusion Detection using Enhanced Classification Technique
... DOS category has the highest representation in the data set. So, most classifiers achieve a good detection rate due to the good training for its attack. Fig 11 and Fig 12 show that our model completely enhances ... See full document
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An Evaluation of Classification and Outlier Detection Algorithms
... and outlier detection (Hodge and Austin 2004) on multi-variate time-series data (Keogh and Kasetty ...an efficient method for on-line classification and outlier detection in mul- ... See full document
5
Data Mining: Evaluation for Intrusion Detection System
... When the rule set stabilizes (there are no new rules added), we can stop the data gathering process since we have produced a near complete set of audit data for the normal runs. We then prune the rule set by eliminating ... See full document
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