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Project 2 PCA
PCA
Project 1 Clustering
Clustering
Document
This project applies a pure dimension reduction approach using t-SNE to the Wine Quality dataset, which consists of physicochemical measurements of red wine samples and corresponding quality ratings assigned by expert tasters. The objective of the analysis is to explore whether wines with similar quality scores exhibit similar physicochemical characteristics when projected into a two-dimensional space
Behavioral Patterns in Cell Phone Reviews (Association Rules)
USL Association Rules Project
Identifying Player Importance Profiles in Professional Basketball - Clustering and Principal Component Analysis of ACB Player Performance
This project applies unsupervised learning to identify distinct and interpretable player importance profiles in the Spanish ACB league in the 2024-25 season, using engineered performance features that go beyond traditional box-score evaluations. By combining clustering and principal component analysis, the study examines whether dimensionality reduction clarifies and stabilizes the structure of player importance without altering the underlying groupings.
rastercontourntif_3rPlot
rastercontourntif_3rPlot
The Social DNA of Cinema (Clustering & Dimension Reduction)
USL Clustering and Dimension Reduction Project
