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PCA_Python_Test.py

dataMatrix2 = P.load('PCA_Matrix_noProE.csv', delimiter = ',', skiprows = 1) #scores, loading, explanation = pca.PCA_nipals2(dataMatrix, standardize=True, E_matrices ...
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[Python Introduction: Principal Component Analysis #4] Quick PCA with scikit-learn - Dimensionality reduction in just 2 lines

In the previous three articles, I explained the mechanism of PCA from scratch. Because you have the experience of manual calculations with NumPy, you understand what the library is doing behind the ...
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SVD-PCA_SGD_MAP_Classifier---Python

a. Lo script carica il dataset "dataSet.npy", composto da $N = 20000$ osservazioni $(X_i, Y_i)$, dove $X_i$ è un vettore di 10 caratteristiche e $Y_i \in {-1, 1}$. b ...
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Mathematical Understanding and Implementation of Principal Component Analysis (PCA) via Covariance Matrices [Python]

While t-SNE is powerful for capturing non-linear relationships, in practical business settings, there is a strong demand for explainability (business justification) regarding "why it was reduced to ...