Research Article

Differentially Private Kernel Support Vector Machines Based on the Exponential and Laplace Hybrid Mechanism

Table 5

The performance of the DPKSVMEL algorithm on dataset Ionosphere.

kɛSimilarityAccuracyAUC
MeanStdMaxMinMeanStdMaxMin

20.10.573.9312.4392.5951.000.94400.01310.96860.9246
0.676.5513.8391.1748.720.93520.02160.97830.9085
0.768.0113.2387.4644.440.94700.01360.96430.9250
0.874.426.2887.1865.810.94380.01470.96730.9226
0.983.964.1190.6077.780.96430.00960.97520.9447

20.50.585.505.9492.8872.360.94410.01590.97010.9195
0.677.819.8892.5960.970.94980.01460.96690.9207
0.782.513.7089.4677.210.94630.01290.97100.9263
0.886.184.9393.1677.490.96100.00610.97170.9514
0.990.512.7792.5984.330.96840.00530.97600.9573

210.589.603.0992.5983.190.96070.01230.97900.9400
0.684.767.8393.4565.810.95980.01010.97530.9466
0.788.806.5293.7373.220.96780.00930.98080.9469
0.893.111.0094.3090.880.97040.00630.97970.9586
0.992.711.7394.3088.600.97510.00360.97990.9698

30.10.579.3211.1790.6055.840.94110.01420.95820.9171
0.674.7611.1793.1654.130.93790.01770.96350.9048
0.773.5611.7291.7455.270.94440.01400.96420.9157
0.877.355.0886.0470.940.95310.01710.97660.9166
0.979.096.1985.4766.670.95750.01230.97250.9408

30.50.582.517.1892.5970.090.94570.02340.97590.8937
0.677.619.3788.3261.540.95670.01620.98010.9328
0.776.8912.8590.3153.850.95800.01100.97170.9410
0.884.766.4392.8876.070.95970.00960.97180.9452
0.989.603.1193.1683.480.97070.00500.98070.9649

310.585.646.9093.4574.930.95390.01350.96870.9299
0.683.4510.6994.0263.250.96510.01020.97490.9382
0.789.263.5592.5982.910.97270.00740.98450.9592
0.891.171.5793.1688.600.97230.00590.98040.9616
0.992.191.8094.3088.600.97570.00500.98170.9648