from sklearn.feature_extraction.text import TfidfVectorizer

from yellowbrick.text import TSNEVisualizer
from yellowbrick.datasets import load_hobbies

# Load the data and create document vectors
corpus = load_hobbies()
tfidf = TfidfVectorizer()

X = tfidf.fit_transform(corpus.data)
tsne = TSNEVisualizer(labels=["documents"])
tsne.fit(X)
tsne.show()