Comparative Study of Different Classification Algorithms for Stream Data Mining Using MOA
DOI:
https://doi.org/10.26438/ijcse/v6i11.614616Keywords:
Stream mining, Hoeffding Tree, Decision Stump, Naive Bayes, Classification, Massive Online Analysis (MOA)Abstract
In the today’s world, the data is much important and it is growing rapidly. It requires some intelligent analysis processing that helps to discover some knowledge from it. These massive data can be processed by the some framework like MOA (Massive Online Analysis). It has predefined data stream mining classification techniques which are used to distribute the data depends on its class. Some of these techniques like Hoeffding Tree, Decision Stump or Naive Bayes are well known. Comparative study of these techniques analyzes same type of data and compares the output. Which gives idea about different algorithms can be used for different purpose
References
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