A hybrid reciprocal model of PCA and K-means with an innovative approach of considering sub-datasets for the improvement of K-means initialization and step-by …
The K-means algorithm is a popular clustering method, which is sensitive to the initialization
of samples and selecting the number of clusters. Its performance on high-dimensional …
of samples and selecting the number of clusters. Its performance on high-dimensional …
Coin: correlation induced clustering for cognition of high dimensional bioinformatics data
Analysis of high dimensional biomedical data such as microarray gene expression data and
mass spectrometry images, is crucial to provide better medical services including cancer …
mass spectrometry images, is crucial to provide better medical services including cancer …
Multiagent system for mutual collaboration classification for cancer detection
A multiagent system (MAS) is a mechanism for creating goal‐oriented autonomous agents in
shared environments with communication and coordination facilities. Distributed data mining …
shared environments with communication and coordination facilities. Distributed data mining …
[PDF][PDF] Using densities to detect nested clusters
R Sane - 2020 - erepo.uef.fi
Clustering is one of the most widely used applications in machine learning. It finds use in
applications like recommendation systems and fraud detection systems. Similar objects are …
applications like recommendation systems and fraud detection systems. Similar objects are …