TESI DOCTORAL - La Salle

B.1.5 Ionosphere data set
Appendix B. Experiments on clustering indeterminacies
As regards the Ionosphere data collection, pretty similar φ (NMI) distributions are obtained
for the PCA, ICA and RP representations (see figures B.5(b) to B.5(d)). Thus, in this
case, there apparently exists a lower dependence between the quality of clustering and the
feature extraction technique used for representing the objects. Nevertheless, despite the
notable concentration of clustering results on the leftmost part of the histograms (i.e. poor
clusterings with low values of φ (NMI) ), there exist some clustering solutions reaching φ (NMI)
values above 0.5 using PCA and ICA feature extraction (see figures B.5(b) and B.5(c)).
Moreover, notice that pretty poor quality clusterings are obtained when operating on the
baseline object representation (figure B.5(a)).
clustering count
150
100
50
Ionosphere Baseline
0
0 0.5 1
φ (NMI)
(a) Baseline
clustering count
150
100
50
Ionosphere PCA
0
0 0.5 1
φ (NMI)
(b) PCA
clustering count
150
100
50
Ionosphere ICA
0
0 0.5 1
φ (NMI)
(c) ICA
clustering count
150
100
50
Ionosphere RP
0
0 0.5 1
φ (NMI)
(d) RP
Figure B.5: Histograms of the φ (NMI) values obtained on each data representation in the
Ionosphere data set.
B.1.6 WDBC data set
As regards the WDBC data collection, there exists a notable difference between the profiles
of the histograms of the PCA, ICA and NMF representations when compared to the
baseline and RP histograms. Indeed, the former present a sharp peak located in the lowest
region of the φ (NMI) range, whereas the latter do not—which reflects the data representation
clustering indeterminacy. The notably large differences between the highest and lowest
φ (NMI) values of all the histograms reveal the influence of the clustering algorithm and data
dimensionality selection on the quality of the partition results.
clustering count
100
50
WDBC Baseline
0
0 0.5 1
φ (NMI)
(a) Baseline
clustering count
100
50
WDBC PCA
0
0 0.5 1
φ (NMI)
(b) PCA
clustering count
100
50
WDBC ICA
0
0 0.5 1
φ (NMI)
(c) ICA
clustering count
100
50
WDBC NMF
0
0 0.5 1
φ (NMI)
(d) NMF
clustering count
100
50
WDBC RP
0
0 0.5 1
φ (NMI)
(e) RP
Figure B.6: Histograms of the φ (NMI) values obtained on each data representation in the
WDBC data set.
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