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What is Clustering Global Development Metrics about?

The project aimed to create clusters for global development measurement using a dataset of 2708 observations and 25 variables. Key steps included exploratory data analysis, feature engineering with PCA, and model building using various clustering algorithms, ultimately deploying a KNN model with 96% accuracy for classifying countries. Challenges included handling missing values, detecting outliers, and selecting appropriate clustering techniques and evaluation metrics.

Author

reddykarishma840

Language

EN