A Comparative Study on TIBA Imputation Methods in FCMdd-Based Linear Clustering with Relational Data

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="265170.fig.005a" src="https://static.hindawi.com/articles/afs/volume-2011/265170/figures/265170.fig.005a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Minimax TIBA (no. missing : 6200)</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="265170.fig.005b" src="https://static.hindawi.com/articles/afs/volume-2011/265170/figures/265170.fig.005b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Maximin TIBA (no. missing : 8000)</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="265170.fig.005c" src="https://static.hindawi.com/articles/afs/volume-2011/265170/figures/265170.fig.005c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b>Average TIBA (no. missing : 7200)</td></tr></table></td></tr></table>

<table>Comparison of cluster partition from incomplete “Kokoro” text data derived with Jaccard’s coefficient imputed by three TIBAs.</table>

Advances in Fuzzy Systems

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Figure 5

Figure 5: A Comparative Study on TIBA Imputation Methods in FCMdd-Based Linear Clustering with Relational Data 