Analysis of global poverty using PCA to identify important parameters and then clustering via both K-means and Hierarchical clustering techniques.
Performed PCA on the dataset and obtain the new dataset with the Principal Components.
Chose the appropriate number of components k.
Performed clustering activity on this new dataset, i.e. the PCA modified dataset with the k components.
Performed the Outlier Analysis on the dataset.
Tried both K-means and Hierarchical clustering (both single and complete linkage) on this dataset to create the clusters.
Analyzed the clusters and identified the ones which are in dire need of aid.