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Research map / Learning theory and algorithms / Kernels and regression theory

TRF: Learning Kernels with Tuned Random Features

AAAI 2022 · Learning theory and algorithms › Kernels and regression theory · approach: Random feature approximation · 1 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use TRF instead of the best listed baselineKernel classification · Biodeg, 20% testmisclassification error (%): 12.0(2.3) -> 11.2(3.5)Helped
Use TRF instead of the best listed baselineKernel classification · Car, 20% testmisclassification error (%): 0.75(0.1) -> 0.73(0.1)Helped
Use TRF instead of the best listed baselineKernel classification · Contra., 20% testmisclassification error (%): 31.6(4.8) -> 29.5(3.1)Helped
Use TRF instead of the best listed baselineKernel classification · Fertility, 20% testmisclassification error (%): 9(4.2) -> 9(4.2)No clear effect
Use TRF instead of the best listed baselineKernel classification · Ionosph., 20% testmisclassification error (%): 3.99(1.6) -> 14.7(7.4)Hurt
Use TRF instead of the best listed baselineKernel classification · Sonar, 20% testmisclassification error (%): 20.5(2.7) -> 15.5(3.2)Helped
Use TRF instead of the best listed baselineKernel classification · a8a, 20% testmisclassification error (%): 12.9(2.7) -> 12.6(2.7)Helped
Use TRF instead of the best listed baselineKernel regression · Airfoil, 20% testRMSE: 0.46(0.02) -> 0.43(0.02)Helped
Use TRF instead of the best listed baselineKernel regression · Auto, 20% testRMSE: 0.17(0.04) -> 0.16(0.03)Helped
Use TRF instead of the best listed baselineKernel regression · Boston, 20% testRMSE: 0.38(0.07) -> 0.38(0.14)No clear effect
Use TRF instead of the best listed baselineKernel regression · Slump, 20% testRMSE: 0.020(0.01) -> 0.018(0.01)Helped
Use TRF instead of the best listed baselineKernel regression · Yatch, 20% testRMSE: 0.05(0.03) -> 0.16(0.12)Hurt

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