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ResearchFormerly WizWand

Policy Decision Making on Synthetic (d_phi=1) out-sample

8.18Error Rate (ER_out)k-NN
7.075614.530321.98529.4397Nov 19, 2023
Updated 7mo ago

Evaluation results

MethodLinks
k-NNNumber of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.118.18—
C-ForestNumber of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1116.1—
BARTNumber of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1117.37—
InvTARNetRepresentation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1129.51-0.95
TARNetRepresentation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1130.79-12.89
RCFR (WM; α = 1.0)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1133.02-3.58
BNN (MMD; α = 0.1)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1134.32-15.41
CFR (WM; α = 1.0)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1134.97-14.27
BWCFR (WM; α = 1.0)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1134.97-10.02
CFR-ISW (WM; α = 1.0)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1135-9.43
CFR (MMD; α = 0.1)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1135.01-14.27
CFR (WM; α = 2.0)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1135.18-13.63
CFR (MMD; α = 0.5)Representation dimension (d_phi)=1, Number of training samples (ntrain)=1,000, Delta parameter (δ)=0.00052023.1135.79-11.43