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Table 2 Classification results (muchmore springer bilingual corpus)

From: A novel multiple kernel fuzzy topic modeling technique for biomedical data

Method AC (%) Precision Recall F1-Score K
LSA [5] 57.65 0.6667 0.7221 0.6933 50
LDA [4] 60.95 0.6938 0.7356 0.7141 50
FKLSA(Entropy) [6] 97.66 0.955 0.9554 0.977 50
FKLSA(IDF) [6] 95.90 0.937 0.935 0.959 50
FKLSA(Normal) [6] 91.22 0.890 0.894 0.912 50
FKLSA(ProbIDF) [6] 97.66 0.954 0.953 0.977 50
FKTM [7] 98.29 0.9880 0.9883 0.9880 50
MKFTM 99.04 0.9975 0.9978 0.9975 50
LSA [5] 56.19 0.6676 0.6791 0.6733 100
LDA [4] 58.85 0.6854 0.7011 0.6932 100
FKLSA(Entropy) [6] 96.49 0.943 0.942 0.965 100
FKLSA(IDF) [6] 98.24 0.961 0.960 0.982 100
FKLSA(Normal) [6] 92.39 0.902 0.900 0.924 100
FKLSA(ProbIDF) [6] 97.66 0.955 0.952 0.977 100
FKTM [7] 98.87 0.9879 0.9841 0.9844 100
MKFTM 99.62 0.9974 0.9936 0.9939 100
LSA [5] 62.67 0.7091 0.7536 0.7285 150
LDA [4] 59.23 0.6991 0.6791 0.6890 150
FKLSA(Entropy) [6] 95.90 0.937 0.935 0.959 150
FKLSA(IDF) [6] 97.66 0.955 0.952 0.977 150
FKLSA(Normal) [6] 95.32 0.932 0.931 0.953 150
FKLSA(ProbIDF) [6] 97.07 0.950 0.952 0.971 150
FKTM [7] 98.97 0.9822 0.9882 0.9886 150
MKFTM 99.69 0.9917 0.9976 0.9980 150
LSA [5] 60.00 0.6980 0.7020 0.9886 200
LDA [4] 63.42 0.7039 0.7765 0.7000 200
FKLSA(Entropy) [6] 97.07 0.950 0.9501 0.7384 200
FKLSA(IDF) [6] 97.66 0.955 0.9553 0.971 200
FKLSA(Normal) [6] 92.39 0.901 0.902 0.977 200
FKLSA(ProbIDF) [6] 97.66 0.955 0.950 0.924 200
FKTM [7] 98.86 0.9883 0.9870 0.977 200
MKFTM 99.61 0.9978 0.9966 0.965 200