Unstructured Data Classification: Uncertain Nearest Neighbor Decision Rule - Softcover

Thippeswamy, Dr. K.; G. S., Dr. Nijaguna

 
9781636480497: Unstructured Data Classification: Uncertain Nearest Neighbor Decision Rule
Softcover
ISBN 10: 1636480497 ISBN 13: 9781636480497
Verlag: Eliva Press, 2020

Inhaltsangabe

According to certain criteria, the classes are identified by using classification techniques, which is considered as data mining tool. When compared with smaller class, the classification results (i.e., accuracy) for bigger class are deviating and the traditional classification procedures provides inaccurate results, which is known as Class Imbalance problem. A class is formed with unequal size, where this type of data is represented and combined as class imbalance data. There are two various categories are presents in class imbalance domain, namely minority (i.e., smaller) and majority (i.e., bigger) classes. The major aim of this research work is to identify the minority class accurately. In this research, two significant methodologies are proposed such as (i) Adaptive-Condensed Nearest Neighbor (ACNN)Algorithm, and (ii) Local Mahalanobis Distance Learning(LMDL) based ACNN algorithm. These methods are significantly improving the imbalanced data classification.

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Verlag
Eliva Press
Erscheinungsdatum
2020
Sprache
Englisch
ISBN 10 
1636480497
ISBN 13 
9781636480497
Einband
Taschenbuch
Anzahl der Seiten
89
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