Abstract:
Healthcare big data is a collection of record
of patient, hospital, doctors and medical treatment
and it is so large, complex, distributed and growing
so fast that this data is difficult to maintain and
analyze using some traditional data analytics tools.
To solve this difficulties, some machine learning tools
are applied on such big amount of data using big
data analytics framework. In recent years, many
researchers have proposed some machine learning
approaches on healthcare data to improve the
accuracy of analytics. These techniques were applied
individually and compared their results. To get better
accuracy, this paper proposes one machine learning
approach called ensemble learning, in which the
results of three machine learning algorithms are
combined. Soft voting method is used for combining
accuracies. From these results, it is observed that
ensemble learning can obtain maximum accuracy.
