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Dimensionality Reduction with PCA Techniques by sumitsingh.nssc is a document available to read on EtoBox.

The document outlines the grading rubric and ethical conduct expectations for an experiment on dimensionality reduction using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) in a machine learning course. It details the process of PCA, including orthogonalization, energy compaction, and error estimation, along with the structure of the dataset used in the experiments. The document emphasizes the importance of independent work and ethical behavior in laboratory settings.

Author
sumitsingh.nssc
Language
EN