Investigate the correlation of breast cancer dataset using different clustering technique
S Chakraborty, B Murali - arXiv preprint arXiv:2109.01538, 2021 - arxiv.org
S Chakraborty, B Murali
arXiv preprint arXiv:2109.01538, 2021•arxiv.orgThe objectives of this paper are to explore ways to analyze breast cancer dataset in the
context of unsupervised learning without prior training model. The paper investigates
different ways of clustering techniques as well as preprocessing. This in-depth analysis
builds the footprint which can further use for designing a most robust and accurate medical
prognosis system. This paper also give emphasis on correlations of data points with different
standard benchmark techniques. Keywords: Breast cancer dataset, Clustering Technique …
context of unsupervised learning without prior training model. The paper investigates
different ways of clustering techniques as well as preprocessing. This in-depth analysis
builds the footprint which can further use for designing a most robust and accurate medical
prognosis system. This paper also give emphasis on correlations of data points with different
standard benchmark techniques. Keywords: Breast cancer dataset, Clustering Technique …
The objectives of this paper are to explore ways to analyze breast cancer dataset in the context of unsupervised learning without prior training model. The paper investigates different ways of clustering techniques as well as preprocessing. This in-depth analysis builds the footprint which can further use for designing a most robust and accurate medical prognosis system. This paper also give emphasis on correlations of data points with different standard benchmark techniques. Keywords: Breast cancer dataset, Clustering Technique Hopkins Statistic, K-means Clustering, k-medoids or partitioning around medoids (PAM)
arxiv.org