A HYBRID ENSEMBLE METHOD FOR ACCURATE FUZZY AND SUPPORT VECTOR MACHINE FOR GENE EXPRESSION IN DATA MINING
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff72e82b00000024ce020001000900
Malignancy is a bunch of infection which spreads all through the human body. Since it is an exceptionally deceptive illness its determination is of vital importance. Information mining innovation helps in arranging and bunching the malignancy information and this procedure assists with distinguishing potential disease patients by investigating the data alone. In this examination we analyze three information mining calculations, namely PCA, Genetic calculation and Hierarchical Fuzzy C Means (HFCM). The hereditary calculation is done using the Quantum-enhanced Support Vector Machine (QSVM). The outcome demonstrates that the proposed calculation accomplishes a better outcome when contrasted to the other two calculations.

Authors
S Vasanthakumar1,N Ranjith2
KSG College of Arts and Science, India1, KSG College of Arts and Science, India2

Keywords
PCA, Genetic Algorithm, Hierarchical Fuzzy C Mean, QSVMs, Cluster
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
000010000000
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 11 , Issue: 4 , Pages: 2444-2448 )
Date of Publication :
July 2021
Page Views :
110
Full Text Views :
1

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.