Table_2.xls (5.5 kB)

Clustering of 10 datasets (generated after performing 10 attribute weighting algorithms) into T (mesophile) and F (thermophile) classes by four different unsupervised clustering algorithms (K-Means, K-Medoids, SVC and EMC).

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posted on 2013-02-20, 15:50 authored by Mansour Ebrahimi, Amir Lakizadeh, Parisa Agha-Golzadeh, Esmaeil Ebrahimie, Mahdi Ebrahimi

The actual numbers of T (mesostable) and F (thermostable) classes in the original datasets were 1544 and 513, respectively. The highest accuracy (100%) was observed when the EMC clustering method was applied to datasets generated by Correlation and Uncertainty attribute weighting algorithms that highlighted in the table.