1. Syskill and Webert Web Page Ratings: This database contains HTML source of web pages plus the ratings of a single user on these web pages. Web pages are on four seperate subjects (Bands- recording artists; Goats; Sheep; and BioMedical)
2. Reuter_50_50: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
3. DBWorld e-mails: It contains 64 e-mails which I have manually collected from DBWorld mailing list. They are classified in: 'announces of conferences' and 'everything else'.
4. YouTube Comedy Slam Preference Data: This dataset provides user vote data on which video from a pair of videos is funnier collected on YouTube Comedy Slam. The task is to automatically predict this preference based on video metadata.
5. SMS Spam Collection: The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research.
6. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.
7. YouTube Multiview Video Games Dataset: This dataset contains about 120k instances, each described by 13 feature types, with class information, specially useful for exploring multiview topics (cotraining, ensembles, clustering,..).
8. Dresses_Attribute_Sales: This dataset contain Attributes of dresses and their recommendations according to their sales.Sales are monitor on the basis of alternate days.
9. microblogPCU: MicroblogPCU data is crawled from sina weibo microblog[http://weibo.com/]. This data can be used to study machine learning methods as well as do some social network research.
10. Miskolc IIS Hybrid IPS: The dataset was created for the comparison and evaluation of hybrid indoor positioning methods. The dataset presented contains data from W-LAN and Bluetooth interfaces, and Magnetometer.
11. DeliciousMIL: A Data Set for Multi-Label Multi-Instance Learning with Instance Labels: This dataset includes 1) 12234 documents (8251 training, 3983 test) extracted from DeliciousT140 dataset, 2) class labels for all documents, 3) labels for a subset of sentences of the test documents.
12. TTC-3600: Benchmark dataset for Turkish text categorization: The TTC-3600 data set is a collection of Turkish news and articles including categorized 3,600 documents from 6 well-known portals in Turkey. It has 4 different forms in ARFF Weka format.
13. YouTube Spam Collection: It is a public set of comments collected for spam research. It has five datasets composed by 1,956 real messages extracted from five videos that were among the 10 most viewed on the collection period.
14. KDC-4007 dataset Collection: KDC-4007 dataset Collection is the Kurdish Documents Classification text used in categories regarding Kurdish Sorani news and articles.
15. Burst Header Packet (BHP) flooding attack on Optical Burst Switching (OBS) Network: One of the primary challenges in identifying the risks of the Burst Header Packet (BHP) flood attacks in Optical Burst Switching networks (OBS) is the scarcity of reliable historical data.
16. Paper Reviews: This sentiment analysis data set contains scientific paper reviews from an international conference on computing and informatics. The task is to predict the orientation or the evaluation of a review.
17. Victorian Era Authorship Attribution: To create the largest authorship attribution dataset, we extracted works of 50 well-known authors. To have a non-exhaustive learning, in training there are 45 authors whereas, in the testing, it's 50
18. Roman Urdu Data Set: Roman Urdu (the scripting style for Urdu language) is one of the limited resource languages.A data corpus comprising of more than 20000 records was collected.
19. Labeled Text Forum Threads Dataset: The dataset is a collection of text forum threads with class labels reflects the reply quality to the Initial-Post, 3 for complete relevant, 2 for partially relevant, and 1 for irrelevant
20. Detect Malware Types: Provide a short description of your data set (less than 200 characters).
21. Opinion Corpus for Lebanese Arabic Reviews (OCLAR): Opinion Corpus for Lebanese Arabic Reviews (OCLAR) corpus is utilizable for Arabic sentiment classification on services’ reviews, including hotels, restaurants, shops, and others.
22. Youtube cookery channels viewers comments in Hinglish: The datasets are taken from top 2 Indian cooking channel named Nisha Madhulika channel and Kabita’s Kitchen channel.
The data set is in Hinglish Language.