Ever since the era of internet had ushered in cloud
computing, there had been increase in the demand for the
unlimited data available through cloud computing for data
analysis, pattern recognition and technology advancement. With
this also bring the problem of scalability, efficiency and security
threat. This research paper focuses on how data can be
dynamically mine in real time for pattern detection in a secure
cloud computing environment using combination of decision tree
algorithm and Random…
Read moreEver since the era of internet had ushered in cloud
computing, there had been increase in the demand for the
unlimited data available through cloud computing for data
analysis, pattern recognition and technology advancement. With
this also bring the problem of scalability, efficiency and security
threat. This research paper focuses on how data can be
dynamically mine in real time for pattern detection in a secure
cloud computing environment using combination of decision tree
algorithm and Random Forest over a restful Application
Programming Interface (API). We are able to successfully
Implement data mining on cloud computing bypassing or
avoiding direct interaction with data warehouse and without any
terminal involve by using combination of IBM Cloud storage
facility, Amazing Web Service, Application Programming
Interface and Window service along with a decision tree and
Random Forest algorithm for our classifier. We were able to
successfully bypass direct connection with the data warehouse
and cloud terminal with 94% accuracy in our model.
