A collection of multi-label and multi-target datasets is available here. Even more datasets are available at the MULAN Website (note that MULAN indexes labels as the final attributes, whereas MEKA indexs as the beginning). See the MEKA Tutorial for more information.

The following text datasets have been created / compiled into WEKA's ARFF format using the StringToWordVector filter. Also available are train/test splits and the original raw prefiltered text.

Dataset L N LC PU Description and Original Source(s)
Enron 53 1702 3.39 0.442 A subset of the Enron Email Dataset, as labelled by the UC Berkeley Enron Email Analysis Project
Slashdot 22 3782 1.18 0.041 Article titles and partial blurbs mined from Slashdot.org
Language Log 75 1460 1.18 0.208 Articles posted on the Language Log
IMDB (Updated) 28 120919 2.00 0.037 Movie plot text summaries labelled with genres sourced from the Internet Movie Database interface, labeled with genres.


  • N = The number of examples (training+testing) in the datasets
  • L = The number of predefined labels relevant to this dataset
  • LC = Label Cardinality. Average number of labels assigned per document
  • PU = Percentage of documents with Unique label combinations