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python-scikit-learnUsing SVD to reduce dimensions example


from sklearn import decomposition, datasets

X, y = datasets.load_iris(return_X_y=True)

svd = decomposition.TruncatedSVD(n_components=2)
svd.fit(X)
X = svd.transform(X)ctrl + c
from sklearn import

import module from scikit-learn

load_iris

loads Iris dataset

.TruncatedSVD(

creates dimensionality reduction model based on truncated SVD

.fit(

train reduction model

.transform(

transform original data and return reduced dimensions data