May 28, 2016 · This paper successfully finds the subtypes of cancers in microarray gene expression cancer database using the proposed method. The superiority ...

Oct 7, 2015 · Effective fuzzy possibilistic c-means: an analyzing cancer medical database. Using clustering analysis for identifying cancer types in high ...

This paper successfully finds the subtypes of cancers in microarray gene expression cancer database using the proposed method. The superiority of the proposed ...

Effective Fuzzy Possibilistic C-Means: An Analyzing Cancer Medical Database · No full-text available · Citations (0) · References (16) · Recommended publications.

Effective fuzzy possibilistic c-means: an analyzing cancer medical database. https://doi.org/10.1007/s00500-016-2198-7 ·. Journal: Soft Computing, 2016, ...

Apr 25, 2024 · Effective fuzzy possibilistic c-means: an analyzing cancer medical database. Soft Comput. 21(11): 2835-2845 (2017); 2015. [j15]. view.

As medical datasets consist of data points which cannot be precisely assigned to a class, fuzzy methods have been useful for studying of these datasets.

In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome the problems ...

The proposed BPCM can discover the underlying patterns in data. •. Propose a fuzzy ensemble learning scheme for cervical cancer screening. Abstract.

This paper shows the effectiveness of the proposed clustering technique in clustering the available classes through benchmark heterogeneous database. The rest ...