Agglomerative-hierarchical-clustering-on-pearson-correlation

The agglomerative hierarchical clustering algorithm is applied to the matrix containing pearson correlation as the distance measure. Here a threshold "delta" is considered before proceeding to clustering. If any of the data values in the pearson matrix is greater than delta, only then clustering is done. Note: Pearson Correlation is inversely related to distance i.e if pearson correlation is more, distance between the instances is less. Finally, the algorithm is evaluated by silhouette coefficient.