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Benchmarks
Tabular Classification with Feature Selection on Heart
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83.11
Accuracy
INVASE
50.2044
58.7472
67.29
75.8328
Aug 4, 2025
Accuracy
Updated 1mo ago
Evaluation Results
Method
Method
Links
Accuracy
INVASE
Selection Strategy=Greedy
2025.08
83.11
ReMLP
Selection Strategy=RL
2025.08
75.08
ReMLP
Selection Strategy=Greedy
2025.08
73.12
CWCF
Selection Strategy=RL
2025.08
70.66
VIP
Selection Strategy=Greedy
2025.08
70.49
CART
Selection Strategy=Greedy
2025.08
70
FTree
Selection Strategy=Greedy
2025.08
68.67
DIME
Selection Strategy=Greedy
2025.08
66.39
Static CMI
Selection Strategy=Static
2025.08
65.58
MLP
Selection Strategy=Greedy
2025.08
65.25
MLP
Selection Strategy=RL
2025.08
64.92
TabNet
Selection Strategy=Static
2025.08
62.3
CART
Selection Strategy=RL
2025.08
61.47
FTree
Selection Strategy=RL
2025.08
51.47
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