Abstract:
The proliferation, ubiquity and increasing power
of computer technology has aided data collection,
processing, management and storage. However, the
captured data needs to be converted into
information and knowledge to become useful. Data
mining is the process of using computing power to
apply methodologies, including new techniques for
knowledge discovery, to data. Data mining identifies
trends within data that go beyond simple data
analysis. Through the use of sophisticated
algorithms, non-statistician users have the
opportunity to identify key attributes of processes
and target opportunities. This paper intends to
support these non-statistician users in analysis of
the cancer diagnosis by implementing the k-means
clustering algorithm. In this paper, the Blood
Cancer diagnosis is analysis in speciality.
