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K-NN Regression on Additive benchmark functions High dependence
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0.0907
Mean ORMSE (f0)
A2D2E
0.079172
0.156986
0.2348
0.312614
Oct 9, 2025
Mean ORMSE (f0)
Mean ORMSE (f1)
Mean ORMSE (f2)
Mean ORMSE (f3)
Mean ORMSE (f4)
Mean ORMSE (f5)
Updated 1mo ago
Evaluation Results
Method
Method
Links
Mean ORMSE (f0)
Mean ORMSE (f1)
Mean ORMSE (f2)
Mean ORMSE (f3)
Mean ORMSE (f4)
Mean ORMSE (f5)
A2D2E
noise fraction=0.3, de...
2025.10
0.0907
0.1956
0.2967
0.206
1.5175
0.2217
PD
noise fraction=0.3, de...
2025.10
0.1161
0.2768
0.3516
0.2038
1.9022
0.2538
ALE
noise fraction=0.3, de...
2025.10
0.122
0.2111
0.3367
0.2821
1.6043
0.2451
DALE
noise fraction=0.3, de...
2025.10
0.1985
0.4132
0.4823
0.4977
1.5721
0.266
M
noise fraction=0.3, de...
2025.10
0.3789
0.3893
0.7958
1.4248
4.305
1.0303
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