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A simple usage of Hierarchical Clustering algorithm to make sense out of World Bank data.

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Hierarchical clustering - World Bank sample dataset

One of the main goals for establishing the World Bank was to fight and eliminate poverty. Continuous evolution and fine-tuning its policies in the ever-evolving world has been helping the institution to achieve the goal of poverty elimination. The barometer of success in the elimination of poverty is measured in terms of improvement of each of the parameters in health, education, sanitation, infrastructure, and other services needed to improve the lives of the poor. The development gains that will ensure the goals must be pursued in an environmentally, socially, and economically sustainable manner.

--Dataset taken from Practical Machine learning Cookbook by Atul Tripathi.

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A simple usage of Hierarchical Clustering algorithm to make sense out of World Bank data.

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