Application of Fuzzy c-Means and Joint-Feature-Clustering to Detect Redundancies of Image-Features in Drug Combinations Studies of BreastCancer

摘要

The high dimensionality of image-based dataset can be a drawback for classification accuracy.In this study, we propose the application of fuzzy c-means clustering, cluster validity indices and thenotation of a joint-feature-clustering matrix to find redundancies of image-features. The introducedmatrix indicates how frequently features are grouped in a mutual cluster. The resulting information canbe used to find data-derived feature prototypes with a common biological meaning, reduce data storageas well as computation times and improve the classification accuracy.