k-means clustering

K mean a metric approach

The approach is to use the k mean methodology to extract cluster  .This metric method permit to choose the number of cluster desired. In our best idea is to use 5 clusters. But to test and analysis , I have selected two to ten classes to verify this first hypothesis and to compare with other results.

The analysis is on individuals and variables.

As previously studied , the individuals analysis is really concentrated on the PCA view . And it s really difficult to have a real data separability. 

The variables clustering is really more interesting. Offering better views. The 5 classes is the most convenient visual choice and best separability offer.

10 clusters

2 clusters

3 clusters

4 clusters

5 clusters

6 clusters

7 clusters

8 clusters

10 clusters

2 clusters

3 clusters

4 clusters

5 clusters

6 clusters

7 clusters

8 clusters

9 clusters