Outlier Detection Using Hybrid Genetic & Bacterial Foraging Algorithm - Kaur, Sharnjeet
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OUTLIER DETECTION USING HYBRID GENETIC AND BACTERIAL FORAGING ALGORITHM: This book gives the overview on outlier and its detection techniques. The Outlier is that data whose specification does not belong to characteristics of dataset or cluster. Dividing objects into meaningful groups of objects or classes (cluster) based on common characteristic play an important role in how people analyses and describe the world. Clustering is the unsupervised learning problem. Better Clustering improves the accuracy of search results and helps to reduce the retrieval time. Present works define various…mehr

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Produktbeschreibung
OUTLIER DETECTION USING HYBRID GENETIC AND BACTERIAL FORAGING ALGORITHM: This book gives the overview on outlier and its detection techniques. The Outlier is that data whose specification does not belong to characteristics of dataset or cluster. Dividing objects into meaningful groups of objects or classes (cluster) based on common characteristic play an important role in how people analyses and describe the world. Clustering is the unsupervised learning problem. Better Clustering improves the accuracy of search results and helps to reduce the retrieval time. Present works define various Algorithms such as Genetic Algorithm and Bacterial Foraging Algorithm to find useful data from outliers data. The research work also throws light on various clustering techniques and types of the cluster.
Autorenporträt
Nome Sharnjeet Kaur, Departamento: C.S.E, Univeridade: Universidade de Chandigarh, Gharaun, Cidade: Kharar, Estado: Punjab, Pincode:140301,País:Índia.