DataCamp

Clustering Wikipedia part I

You saw in the video that TruncatedSVD is able to perform PCA on sparse arrays in csr_matrix format, such as word-frequency arrays. Combine your knowledge of TruncatedSVD and k-means to cluster some popular pages from Wikipedia. In this exercise, build the pipeline. In the next exercise, you'll apply it to the word-frequency array of some Wikipedia articles.

Create a Pipeline object consisting of a TruncatedSVD followed by KMeans. (This time, we've precomputed the word-frequency matrix for you, so there's no need for a TfidfVectorizer).

The Wikipedia dataset you will be working with was obtained from here.

Import:
- TruncatedSVD from sklearn.decomposition.
- KMeans from sklearn.cluster.
- make_pipeline from sklearn.pipeline.
Create a TruncatedSVD instance called svd with n_components=50.
Create a KMeans instance called kmeans with n_clusters=6.
Create a pipeline called pipeline consisting of svd and kmeans.

Take Hint (-30 XP)

Exercise

Clustering Wikipedia part I

Instructions