LDA topic number selection and Can the model use on multi label classification task?

[kaohaochuan]

@kaize0409

Thanks your fantastic work !

Hello ! I can use the generate_LDA.py now! But I still have something confused! parser.add_argument('--topn', type=int, default=10, help='top n keywords') parser.add_argument('--topics', type=int, help='number of topics')

I know --topn is like your paper mention that top K words right? But How to determine the number of --topics ? The number of labels? Can if I use --topics 20 on R8 dataset, it will be error like scipy.sparse.coo_matrix . So like R8 has --topics :8 R52 has --topics :52 I'm nor really sure:(

Also I am trying to modify the framework of HyperGAT to fit on my Chinese multi label text classification data. Which have approximately 2500 text with 9 labels. Have you ever try your HyperGAT on multi label classification task? such like Kaggle's toxic comment classification datasets ?