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Using k-means clustering approaches to reduce intraclass variability. We have assessed a traditional clustering pipeline (feature extraction + dimensionality reduction with AE's + K-Means).

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Name		Name	Last commit message	Last commit date
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.ipynb_checkpoints		.ipynb_checkpoints
Rscript		Rscript
autoencoders		autoencoders
hopkins		hopkins
resources		resources
silhouette		silhouette
.gitignore		.gitignore
README.md		README.md
k-means.py		k-means.py

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ClusteringAnalysis

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Using k-means clustering approaches to reduce intraclass variability. We have assessed a traditional clustering pipeline (feature extraction + dimensionality reduction with AE's + K-Means).

clustering plants autoencoders k-means-clustering

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