principal_components

principal_components, demonstrates the method of Principal Components.

The notes:

• principal_components.pdf
• principal_components.tex

Scripts:

• svd_approx.py, shows how a matrix A can be approximated using a sum of outer products based on the SVD.
• svd_6x4.py, uses SVD to carry out PCA on a random 6x4 matrix.
• svd_glass.py, uses SVD to carry out PCA on glass data.
• svd_image.py, uses SVD to carry out PCA on an image.
• svd_product.py, verififes that A = U * S * V.

Text Files:

• concrete_data.txt, a data file of concrete properties, used for the homework.
• glass_data.txt, a data file of glass properties.
• svd_6x4.txt, the output file from svd_6x4().

Images:

• casablanca.png
• components.png
• svd_glass_percentage.png,
• svd_glass_singular_values.png,
• svd_image_1.png,
• svd_image_2.png,
• svd_image_3.png,
• svd_image_4.png,
• svd_image_5.png,
• svd_image_6.png,