Supervised hybrid feature selection based on PSO and rough sets for medical diagnosis
Medical datasets are often classified by a large number of disease measurements and a
relatively small number of patient records. All these measurements (features) are not …
relatively small number of patient records. All these measurements (features) are not …
Hybrid Tolerance Rough Set–Firefly based supervised feature selection for MRI brain tumor image classification
G Jothi - Applied Soft Computing, 2016 - Elsevier
Brain tumor is one of the most harmful diseases, and has affected majority of people
including children in the world. The probability of survival can be enhanced if the tumor is …
including children in the world. The probability of survival can be enhanced if the tumor is …
A novel hybrid feature selection method based on rough set and improved harmony search
HH Inbarani, M Bagyamathi, AT Azar - Neural Computing and Applications, 2015 - Springer
Feature selection is a process of selecting optimal features that produce the most prognostic
outcome. It is one of the essential steps in knowledge discovery. The crisis is that not all …
outcome. It is one of the essential steps in knowledge discovery. The crisis is that not all …
A review on soft set-based parameter reduction and decision making
Many real world decision making problems often involve uncertainty data, which mainly
originating from incomplete data and imprecise decision. The soft set theory as a …
originating from incomplete data and imprecise decision. The soft set theory as a …
Intelligent system for feature selection based on rough set and chaotic binary grey wolf optimisation
Feature Selection (FS) has a non-trivial role in supervised learning; like classification, for
many causes. FS aims at facilitating the model processes and reducing the computation …
many causes. FS aims at facilitating the model processes and reducing the computation …
Hybrid rough-bijective soft set classification system.
HH Inbarani, SU Kumar, AT Azar… - Neural Computing & …, 2018 - search.ebscohost.com
In today's medical world, the patient's data with symptoms and diseases are expanding
rapidly, so that analysis of all factors with updated knowledge about symptoms and …
rapidly, so that analysis of all factors with updated knowledge about symptoms and …
Modified dominance-based soft set approach for feature selection
Big data analysis applications in the field of medical image processing have recently
increased rapidly. Feature reduction plays a significant role in eliminating irrelevant features …
increased rapidly. Feature reduction plays a significant role in eliminating irrelevant features …
Efficient feature selection technique for brain tumor classification utilizing hybrid fruit fly based abc and ann algorithm
D Kapila, N Bhagat - Materials Today: Proceedings, 2022 - Elsevier
In medical science, information technology plays a main role in image processing for
medicinal investigation and classification. For this reason “Magnetic Resonance …
medicinal investigation and classification. For this reason “Magnetic Resonance …
Soft computing approaches based bookmark selection and clustering techniques for social tagging systems
A Tolba, E Elashkar - Cluster Computing, 2019 - Springer
Big Data analysis is the era of goliath measures of data more than a brief stage like social
tagging framework. Social tagging frameworks such as BibSonomy and del. icio. us have …
tagging framework. Social tagging frameworks such as BibSonomy and del. icio. us have …
Tolerance rough set firefly-based quick reduct
J Ganesan, HH Inbarani, AT Azar, K Polat - Neural Computing and …, 2017 - Springer
In medical information system, there are a lot of features and the relationship among
elements is solid. In this way, feature selection of medical datasets gets awesome worry as …
elements is solid. In this way, feature selection of medical datasets gets awesome worry as …