A survey of outlier detection algorithms for data streams
J Tamboli, M Shukla - 2016 3rd international conference on …, 2016 - ieeexplore.ieee.org
Data mining is characterized as the process of examining hidden patterns and outlining into
some useful information. It is an exciting field of research for researchers. Data streams are …
some useful information. It is an exciting field of research for researchers. Data streams are …
Activated carbon-ZnO nanocomposite for electrochemical sensing of acetaminophen
In this work, we reported the preparation of AC-ZnO by using simple chemical co-
precipitation and ultrasonication techniques and investicated the electrocatalytic behaviour …
precipitation and ultrasonication techniques and investicated the electrocatalytic behaviour …
Empirical analysis and improvement of density based clustering algorithm in data streams
Data mining has gained much importance in the field of research these days. It makes
perfect blend for analyzing data of any fields and provide decision based output. Data …
perfect blend for analyzing data of any fields and provide decision based output. Data …
Consolidated study & analysis of different clustering techniques for data streams
Recently a data mining particularly a stream data has been drawing widespread attentions
of the researchers and the experts around the globe and a huge number of interesting …
of the researchers and the experts around the globe and a huge number of interesting …
[PDF][PDF] Outlier Detection in Data Streams Using Fuzzy C-Mean Clustering, Outlier Detection and Genetic Algorithm
P Giri, A Raghuvanshi, MIT Ujjain - International Journal for Rapid …, 2016 - ijrretas.com
Outliers with the rest of the data points which are different from or inconsistent. New novel,
unusual, abnormal or may contain noise. Outliers are sometimes more interesting than the …
unusual, abnormal or may contain noise. Outliers are sometimes more interesting than the …