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Trends of fitness values on high-dimensional datasets.

Trends of fitness values on high-dimensional datasets.

<p>The figure shows the trend of fitness values and ACC over the number of iterations on 8 high-dimensional datasets.</p>

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Bibliographic Details
Main Author: Xiaotong Bai (19819284) (author)
Other Authors: Yuefeng Zheng (19819287) (author), Yang Lu (59885) (author), Yongtao Shi (8684100) (author)
Published: 2024
Subjects:
Genetics
Molecular Biology
Biotechnology
Evolutionary Biology
Cancer
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
solving complex problems
random disturbance factors
population variations rich
dimension reduction rate
average classification accuracy
hybrid algorithms formed
combining filter algorithms
experimental results show
drr reached 41
div >< p
>< sub xmlns
candidate feature subset
feature selection
average value
wrapper algorithms
single algorithms
candidate features
vary randomly
using relieff
two stages
tmkmcrigwo ).
three sets
reaches 24
ranked using
optimal subset
generalization ability
dimensional datasets
comparison experiments
also shows
8 high
76 %.
20 datasets
12 low
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