How to do SVD with Dask?

How to do SVD with Dask?

How to do SVD with Dask?

This recipe helps you do SVD with Dask


Recipe Objective

How to do SVD with Dask?

SVD stands for Singular value Decomposition. This transformer performs linear dimensionality reduction by means of truncated singular value decomposition (SVD).

Step 1- Importing Libraries.

import dask.array as da import dask from dask_ml.decomposition import TruncatedSVD import dask.array as da

Step 2- Instantiating SVD.

svd = TruncatedSVD(n_components=5, n_iter=3, random_state=42)

Step 3- Printing explained variance ratio sum.


Additional Info.

Visualizing how this tranformer works.

X = da.random.random((100, 10), chunks=(50, 10)).persist() x, y, z = da.linalg.svd(X) dask.visualize(x, y, z)

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