Mathematical Problems in Engineering / 2015 / Article / Tab 2

Research Article

Sample-Based Extreme Learning Machine with Missing Data

Table 2

Classification performance comparisons over different missing ratios on the UCI benchmark data sets. Performance includes mean aggregate accuracy ± standard deviation and training time (in seconds).

S-ELM ZF-ELM MF-ELM

Breast cancer 0.7185 ± 0.01510.6570 ± 0.03340.6901 ± 0.0183
0.34730.27760.2947

Diabetes 0.7375 ± 0.02630.6852 ± 0.04670.6957 ± 0.0448
0.93150.72570.7112

Flare solar 0.5635 ± 0.02170.5369 ± 0.03480.5454 ± 0.0441
2.9382.1082.272

German 0.7624 ± 0.02500.6984 ± 0.03010.7150 ± 0.0257
3.7482.3272.374

Splice 0.6704 ± 0.06020.5734 ± 0.02750.5916 ± 0.0273
10.8311.269.273

Waveform 0.8287 ± 0.02360.7206 ± 0.02710.7456 ± 0.0314
120.599.26108.5

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