Why Naive Ensembles Do Not Work in Cloud Computing

One of the greatest challenges of data mining is dealing with very large datasets. Cloud computing has demonstrated great advantages in processing very large datasets. When considering taking advantage of the high performance data cloud to do data mining, there are different approaches to make an existing data mining algorithm parallelizable in a cloud computing environment. One concern is how to achieve better performance by making use of the data in a more intelligent way. In this paper, we describe two different approaches to parallelize the existing random decision tree mining algorithm, which we have built on the sector/sphere cloud computing environment. We compare the cost and accuracy between those two different implementations and analyze the result of this experimental study.