I apply a K-mean algorithm to classify some text documents using scikit learn and display the clustering result. I would like to display the similarity of my cluster in a similarity matrix. I didn't see any tool in the scikit learn library that allows to do so.
# headlines type: <class 'numpy.ndarray'> tf-idf vectors
pca = PCA(n_components=2).fit(headlines)
data2D = pca.transform(to_headlines)
pl.scatter(data2D[:, 0], data2D[:, 1])
km = KMeans(n_clusters=4, init='k-means++', max_iter=300, n_init=3, random_state=0)
km.fit(headlines)
Is there any way/library that will allow me to draw easily this cosine similarity matrix?