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erdogant
pca: A Python Package for Principal Component Analysis.
Python 3.11.4 Pandas 2.0.3 pca 2.0.3 Code: ```python from sklearn.datasets import load_wine import pandas as pd from pca import pca pd.options.mode.copy_on_write = True data = load_wine() df = pd.DataFrame(index=data.target, data=data.data,...
hi! thank you for developing this neat package. Do you have any plans to implement some way to select the optimal numbers of PCs based on various methods such as:...
there is this repo that brought up the ideas of a transformation based on increasing variance. https://github.com/alfredsasko/advanced-principle-component-analysis If maximizing variance and maximizing independence between factors look so similar, what could...
Hello, I've tried your PCA package, It's great and I want to say : Thank you for your efforts So, I'm looking for the [NIPALS](https://cran.r-project.org/web/packages/nipals/vignettes/nipals_algorithm.html) decomposition method Because in our...
Currently I am awaiting datasets with a data format of "liked items by user", and that certain items are similar in nature. Currently there are a few ways of reducing...
Hi Erdogant, Is there a build-in functionality to plot an ellipsoid in a 3D scatter plot? I want to use the three most significant components of my data to do...
For fun I also borrowed some other data from [This Link](https://osf.io/dbn4k) and see how personality and test performance can be condensed to a dimensionally reduced model. [personality_score.csv](https://github.com/erdogant/pca/files/9858247/personality_score.csv) Question1 : what...
Hi @erdogant , I was thinking that it would be interesting to have access to other types of PCA, more specifically, for dealing with binary data such as this library:...
