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Feature importance score based on information gain and feature selection frequency.

Feature importance score based on information gain and feature selection frequency.

<p>Feature importance score based on information gain and feature selection frequency.</p>

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Bibliographic Details
Main Author: Guomei Cui (20721578) (author)
Other Authors: Chuanjun Wang (14802747) (author)
Published: 2025
Subjects:
Plant Biology
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
support vector machine
convolutional neural network
commonly used algorithms
gradient boosting tree
ensemble learning methods
real game data
decision tree optimization
sprint pattern recognition
decision tree
pattern recognition
tree structure
existing methods
recognition ability
data collected
xlink ">
training data
thus reducing
test set
super parameters
study come
study aims
stride length
step frequency
sports states
simulation environment
reasonable selection
random forest
precision sensors
may deviate
generalization ability
gbt ),
future research
fitting phenomenon
computer simulation
competition strategies
adaptively adjusting
9 %,
0 %).
0 %)
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