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pythonvarianceeigenvector

How to obtain standard deviation and proportion of variance from eigenvector eigenvalues

How to obtain standard deviation and proportion of variance from eigenvector eigenvalues ? Il like to implement the calculation in Python.

Thanks

Solution

  • There's an easy way to calculate the relative contribution of each eigenvalue/vector in your data using sklearn in python. 

    import numpy as np
from sklearn.decomposition import PCA
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
pca = PCA(n_components=2)
pca.fit(X)

    the pca object has an attribute called explained variance, which shows the proportion of variance from each eigenvector. 

    print(pca.explained_variance_ratio_)

    See http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html for more details.