Biological Subtyping in Psychiatry: Hope, Controversy, and A New Method
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Covers the principles and methods of clustering in machine learning, including similarity measures, PCA projection, K-means, and initialization impact.
Introduces machine learning basics, covering data segmentation, clustering, classification, and practical applications like image classification and face similarity.
Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.
