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So, there exists a correspondence relationship between the clustering accuracy and the correct clustering number.

Now, when σ takes different values, the relationships between k and the clustering accuracy of five data sets are discussed below, which are shown in Fig. 6.

Interestingly, for the rank-based method, the clustering accuracy is almost invariant for rank cutoffs between 2 and 8. Figure 4 d) shows the best accuracy that can be achieved on the three types of networks.

Experimental results indicate that the DLSIAC is superior to other five clustering algorithms on the optimum number of clusters found and the clustering accuracy.

The clustering accuracy obtained by our proposed clustering algoritm outperformes the standard k-means clustering algorithm.

Thus, (M phi -distance M phi -distanceially imeasure the clusubstantiallyacy.

This parameter greatly influences the clustering accuracy, as measured by the Rand index, of the final clusters produced.

Three distance functions were tried to investigate the clustering accuracy.

SNF can obtain better classification accuracy (93 %) but the clustering accuracy is unsatisfied.

As shown in Table 6, the correct clustering number and the satisfied clustering accuracy can be obtained.

With selected features falling between 10 and 180, experimental results showed that Isomap achieves the best clustering accuracy on our datasets.