Correlation-Based Ensemble Feature Selection Using Bioinspired Algorithms and Classification Using Backpropagation Neural Network

Table 6

Feature importance of WDBC dataset.

S. no.	Feature	Feature importance	Rank
1	ID	0.852635	24
2	Radius (mean)	0.860782	22
3	Radius (error)	0.835712	27
4	Radius (worst)	0.926704	10
5	Texture (mean)	0.928031	8
6	Texture (error)	0.776179	29
7	Texture (worst)	0.909129	16
8	Perimeter (mean)	0.93506	2
9	Perimeter (error)	0.94209	1
10	Perimeter (worst)	0.735037	30
11	Area (mean)	0.836177	26
12	Area (error)	0.933734	5
13	Area (worst)	0.864297	20
14	Smoothness (mean)	0.931545	6
15	Smoothness (error)	0.925377	11
16	Smoothness (worst)	0.93505	3
17	Compactness (mean)	0.923189	12
18	Compactness (error)	0.928030	9
19	Compactness (worst)	0.858593	23
20	Concavity (mean)	0.818137	28
21	Concavity (error)	0.917486	14
22	Concavity (worst)	0.900307	17
23	Concave (mean)	0.863435	21
24	Concave (error)	0.898584	18
25	Concave (worst)	0.935045	4
26	Symmetry (mean)	0.719719	31
27	Symmetry (error)	0.918347	13
28	Symmetry (worst)	0.930219	7
29	Fractal dimension (mean)	0.914832	15
30	Fractal dimension (error)	0.845395	25
31	Fractal dimension (worst)	0.891554	19