| Type of Material: | Thesis |
| Title: | Efficient and effective clustering algorithms by using sampling techniques for imbalanced data |
| Researcher: | Naga Santosh Kumar Ch. |
| Guide: | Govardhan A. | Nageswara Rao K. |
| Department: | Faculty of Computer Science and Engineering |
| Publisher: | Jawaharlal Nehru Technological University, Hyderabad |
| Place: | Hyderabad |
| Year: | 2016 |
| Language: | English |
| Subject: | Algorithms | Clustering | Samping techniques | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Faculty of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Hyderabad; 2016 |
| Fulltext: | Shodhganga |
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| 008 | __ | 240726t2016||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_454200 |
| 040 | __ | |aJNTU_500028|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aNaga Santosh Kumar Ch.|eResearcher |
| 110 | __ | |aFaculty of Computer Science and Engineering|bJawaharlal Nehru Technological University, Hyderabad|dHyderabad|ein|0U-0017 |
| 245 | __ | |aEfficient and effective clustering algorithms by using sampling techniques for imbalanced data |
| 260 | __ | |aHyderabad|bJawaharlal Nehru Technological University, Hyderabad|c2016 |
| 300 | __ | |dDVD |
| 502 | __ | |cFaculty of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Hyderabad|d2016|bPhD |
| 518 | __ | |dJune 2016|oDate of Award |
| 518 | __ | |oDate of Registration|d2009-01-01 |
| 520 | __ | |aData mining and Knowledge discovery is the process of discovering hidden knowledge from the datasets. In data mining thenewlinemain approaches are supervised and unsupervised learning. In unsupervised learning k-means is one of the benchmark algorithms.newlineAmong the various real world data sources, many of the applications have the imbalance data and the imbalance data learning is one of the emerging fields of research which draws a special attention because of its significance. The present research have investigated through the area of this problem with a deeper insightnewlineand found that there is still a great/ broad scope to propose novel and efficient unsupervised algorithms for better knowledge mining from data. The data mining research community is facing a burning challenge in Class Imbalance Learning (CIL) in unsupervised learningnewlinedomain. The problem of class imbalance learning is of great significance when dealing with the real-world datasets. The data imbalance problem is more serious i |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aAlgorithms |
| 653 | __ | |aClustering |
| 653 | __ | |aSamping techniques |
| 700 | __ | |aGovardhan A.|eGuide |
| 700 | __ | |eCo-Guide|aNageswara Rao K. |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/287860|yShodhganga |
| 905 | __ | |afromsg |
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