Table_2.xls (5.5 kB)
Download file

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).

Download (0 kB)
posted on 20.02.2013, 15:50 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.