Clustering (ML)
2021 Clustering of Outside Hitters based on performance indexes - Clustering (ML)
2021 Clustering of Outside Hitters based on performance indexes - Clustering (ML)
Several clustering algorithms were used to cluster outside hitters based on their attack, reception, and serve performances
The work includes a standardization of the performance indexes to compare players with different amount of data available
Results from several clustering models (K-Means, Agglomerative Clustering, Spectral Clustering, DBSCAN, Mean Shift) are displayed for a 2-feature and 3-feeature analysis (with same weight)
The data-set consists of 2021 summer national team season (Volleyball Nations League and Tokyo Olympics)
This work was developed with Python in a Jupyter Notebook, using Pandas and scikit-learn, with Plotly as visualization library
Scroll below to see process and results
