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Exploratory project: applied K-means clustering and PCA to CLIP embeddings from the Natural Scenes Dataset (NSD), exploring challenges in clustering high-dimensional, complex data. Limited clustering results, t-SNE and UMAP visualizations provided insights, showing limitations of centroid-based methods and potential for other approaches.
fishtangerine/public_final_project_COGS199
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Exploratory project: applied K-means clustering and PCA to CLIP embeddings from the Natural Scenes Dataset (NSD), exploring challenges in clustering high-dimensional, complex data. Limited clustering results, t-SNE and UMAP visualizations provided insights, showing limitations of centroid-based methods and potential for other approaches.
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