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Table 4 Description of five selected machine learning data

From: Entropy clustering-based granular classifiers for network intrusion detection

Data setsGlass dataE-coli dataLonosphere dataDiabetes dataBanana data
LDA [25]77.6288.12Null76.6076.60
SVM+LD A[25]79.1788.29Null76.5853.03
SV M[24]74.81 ± 0.6487.28 ± 0.3695.71 ± 0.0276.76 ± 0.0889.40 ± 0.02
KN N[22]72.00*NullNullNullNull
TS-KN N[22]80.40NullNullNullNull
The proposed ECGC1.1. 84.26 ± 1.601.2. 90.77 ± 0.081.3. 96.60 ± 0.241.4. 78.12 ± 0.231.5. 89.56 ± 0.12
  1. *Null represents the results of the model are unknown