NLP, Python, Scikit Learn.
300.000 values (6000 words). This time, KMeans showed a surprise: When using the 300.000 length vectors, all documents are put into one cluster as well: x_train_padded = pad_word_vectors(x_train,300000) n_clusters = 5 model = KMeans(n_clusters, random_state=0, n_init="auto").fit(x_train_padded )