  In this age of Big Data, machine learning based data mining methods are
extensively used to inspect large scale data sets. Deriving applicable
predictive modeling from these type of data sets is a challenging obstacle
because of their high complexity. Opportunity with high data availability
levels, automated classification of data sets has become a critical and
complicated function. In this paper, the power of applying MapReduce based
Distributed AdaBoosting of Extreme Learning Machine (ELM) are explored to build
reliable predictive bag of classification models. Thus, (i) dataset ensembles
are build; (ii) ELM algorithm is used to build weak classification models; and
(iii) build a strong classification model from a set of weak classification
models. This training model is applied to the publicly available knowledge
discovery and data mining datasets.
