Table 4 Comparison of proposed algorithm with advanced methods while using breast cancer data sets.

From: SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study

References

Algorithms

Accuracy

Training Time

Testing time

Proposed method

SGA + RF

99.01

3.25 s

240.9 Ms

4

mRMR + SSO + WSVM

99.62

4.81s

355.6 Ms

36

NB + KNN

97.51

3.36 s

334.59 Ms

37

IQI-BGWO-SVM

98.96

3.89 s

258.01 Ms

38

ACO + PSO

97.14

4.18 s

328.89 Ms

39

EOSA + CNN

98.30

3.43 s

272.9 Ms

40

SOLO

88.46

2.27 s

382.9 Ms

41

BiCNN

97.01

3.78 s

244.2 Ms

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