Downloads: 107
M.Tech / M.E / PhD Thesis | Information Technology | India | Volume 3 Issue 7, July 2014
Hybrid Approach for Outlier Detection in High Dimensional Dataset
Rohini Balkrishna Gurav, Sonali Rangdale
An object that does not obey the behavior of normal data objects is called as Outlier. In many data analysis process, a large number of data are being recorded or sampled as data set. It is very important in data mining to find rare events, anomalies, exceptions etc. Outlier detection has important applications in many fields in which the data can contain high dimensions. Resulting the intended knowledge of outliers will become inefficient and even infeasible in high dimensional space. I devised an outlier detection structure which is based on clustering. Clustering is an unsupervised type of data mining and it does not require trained or labeled data. Combination of density based and partition clustering method for taking improvement of both densities based and distance based outlier detection. Weights are allocated to attributes depending upon their individual significance in mining task and weights are adaptive in nature. Weighted attributes are useful to reduce or remove the effect of noisy attributes. In view of the challenges of streaming data, the schemes are incremental and adaptive to concept development. In high dimensional data the number of attributes associated with the dataset is very large and it makes the dataset unmanageable. Thus a Feature Extraction technique is used to reduce the number of attributes to a manageable value.
Keywords: Attribute weighting, Dataset, DBSCAN, k-mean, unsupervised method
Edition: Volume 3 Issue 7, July 2014
Pages: 1743 - 1746
How to Cite this Article?
Rohini Balkrishna Gurav, Sonali Rangdale, "Hybrid Approach for Outlier Detection in High Dimensional Dataset", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=20071403, Volume 3 Issue 7, July 2014, 1743 - 1746
Similar Articles with Keyword 'Dataset'
Downloads: 95
Survey Paper, Information Technology, India, Volume 3 Issue 6, June 2014
Pages: 1479 - 1482Analysis of NSL-KDD Dataset for Fuzzy Based Intrusion Detection System
Macdonald Mukosera, Thabiso Peter Mpofu, Budwell Masaiti
Downloads: 103
Research Paper, Information Technology, India, Volume 4 Issue 4, April 2015
Pages: 2734 - 2737Detection of Outliers Using Hybrid Algorithm on Categorical Datasets
Rachana P. Jakkulwar, Prof. R. A. Fadnavis
Downloads: 103
Research Paper, Information Technology, India, Volume 4 Issue 6, June 2015
Pages: 2493 - 2496An Effective Up-Growth Algorithm for Discovering High Utility Itemset Mining
Anuja Palhade, Rashmi Deshpande
Downloads: 105
Research Paper, Information Technology, India, Volume 3 Issue 6, June 2014
Pages: 1654 - 1660Privacy Preserving Protocol for Two-Party Classifier Over Vertically Partitioned Dataset Using ANN
Smitha Iddalgave, Sumana M
Downloads: 105
M.Tech / M.E / PhD Thesis, Information Technology, India, Volume 4 Issue 3, March 2015
Pages: 2441 - 2444Privacy-Preservation of Centralized and Distributed Social Network by Using L-Diversity Algorithm
Shankaranand, P. Rajasekar
Similar Articles with Keyword 'k-mean'
Downloads: 107
M.Tech / M.E / PhD Thesis, Information Technology, India, Volume 3 Issue 7, July 2014
Pages: 1743 - 1746Hybrid Approach for Outlier Detection in High Dimensional Dataset
Rohini Balkrishna Gurav, Sonali Rangdale
Downloads: 108
Research Paper, Information Technology, India, Volume 4 Issue 4, April 2015
Pages: 988 - 991GPU Accelerated Clustering Techniques
Komal D. Nistane, Shailendra W. Shende
Downloads: 109 | Weekly Hits: ⮙5 | Monthly Hits: ⮙12
Comparative Studies, Information Technology, India, Volume 5 Issue 4, April 2016
Pages: 2013 - 2019Comprehensive Research on Privacy Preserving Emphasizing on Distributed Clustering
Prajna M.S., Sumana M.
Downloads: 119
Research Paper, Information Technology, India, Volume 4 Issue 9, September 2015
Pages: 876 - 880Mining GPS Data for Traffic Congestion Detection and Prediction
Suhas Prakash Kaklij
Downloads: 127 | Weekly Hits: ⮙2
Research Paper, Information Technology, India, Volume 5 Issue 1, January 2016
Pages: 337 - 344Bootstrapping in Text Mining Applications
C. K. Chandrasekhar, M. R. Srinivasan, B. Ramesh Babu