EURASIP Journal on Image and Video Processing

Table 5 Predictability comparisons on NUS-WIDE-LITE

From: SIP-FS: a novel feature selection for data representation

Algorithms	mRMR	ReliefF	En-mRMR	En-ReliefF	SIP-FS
Birds	0.733	0.686	0.717	0.625	0.725
Boats	0.694	0.653	0.673	0.628	0.702
Flowers	0.834	0.804	0.834	0.808	0.824
Rocks	0.732	0.666	0.735	0.688	0.754
Sun	0.820	0.827	0.807	0.801	0.825
Tower	0.760	0.652	0.749	0.652	0.739
Toy	0.726	0.710	0.733	0.698	0.714
Trees	0.701	0.660	0.688	0.654	0.699
Vehicle	0.761	0.745	0.754	0.687	0.773
Average	0.751	0.711	0.743	0.693	0.751

The top performance in each row is highlightened in boldface

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