Factor Loadings using sklearn Question: I want the correlations between individual variables and principal components in python. I am using PCA in sklearn. I don’t understand how can I achieve the loading matrix after I have decomposed my data? My code is here. iris = load_iris() data, y = iris.data, iris.target pca = PCA(n_components=2) transformed_data …
How to get the 1st Principal Component by PCA using Python? Question: I have a set of 2D vectors presented in a n*2 matrix form. I wish to get the 1st principal component, i.e. the vector that indicates the direction with the largest variance. I have found a rather detailed documentation on this from Rice …
Principal Component Analysis (PCA) in Python Question: I have a (26424 x 144) array and I want to perform PCA over it using Python. However, there is no particular place on the web that explains about how to achieve this task (There are some sites which just do PCA according to their own – there …
Principal component analysis in Python Question: I’d like to use principal component analysis (PCA) for dimensionality reduction. Does numpy or scipy already have it, or do I have to roll my own using numpy.linalg.eigh? I don’t just want to use singular value decomposition (SVD) because my input data are quite high-dimensional (~460 dimensions), so I …
