This assignment uses the Country Data file, which contains metrics used in a recent happiness index of most countries in the world.
The three variables in the dataset are Log GDP per capita (a measure of the average economic output per person in the country), Social Support Rating (a rating between 0 and 1 indicating the availability of publicly funded services to support citizens needing help), and Healthy Life Expectancy (the average number of healthy years a person born today in the country will live). All three variables tend to be positively correlated with happiness; higher numbers are associated with higher average self-reported happiness by citizens of the country.
Import the dataset into RapidMiner, excluding the Country column. You should only be importing columns B:D.
1.Build a process that normalizes the data using a 0-1 range transformation and runs k-means clustering with k=4 on the data set. (Be sure to check the determine good start values box and use a local random seed of 12345.) Show a screenshot of the Process panel.
2.Run the process. Show a screenshot of the centroid table.
3.Based on the centroid table, describe the four types of countries that are revealed by these clustering results. (Describe them in words; do not simply report the numbers in the table.)
4.Add the Cluster Model Visualizer operator to your process. Show a screenshot of the heat map that it produces for your clusters.
Please follow the requirements and save this assignment to a Word file. The Country Data excel file is attached below. Thank you
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