Center for Machine Learning and Intelligent Systems
About  Citation Policy  Donate a Data Set  Contact


Repository Web            Google
View ALL Data Sets

Browse Through:

Default Task - Undo

Classification (12)
Regression (0)
Clustering (4)
Other (2)

Attribute Type

Categorical (1)
Numerical (4)
Mixed (0)

Data Type - Undo

Multivariate (39)
Univariate (3)
Sequential (7)
Time-Series (10)
Text (12)
Domain-Theory (1)
Other (2)

Area - Undo

Life Sciences (3)
Physical Sciences (1)
CS / Engineering (21)
Social Sciences (5)
Business (4)
Game (0)
Other (12)

# Attributes

Less than 10 (6)
10 to 100 (2)
Greater than 100 (0)

# Instances

Less than 100 (0)
100 to 1000 (4)
Greater than 1000 (6)

Format Type

Matrix (5)
Non-Matrix (7)

12 Data Sets

Table View  List View


1. Badges: Badges labeled with a "+" or "-" as a function of a person's name

2. CLINC150: This is a intent classification (text classification) dataset with 150 in-domain intent classes. The main purpose of this dataset is to evaluate various classifiers on out-of-domain performance.

3. Guitar Chords finger positions: Position of the fingers for 2633 guitar chords in standard tuning (double checked with software)

4. Russian Corpus of Biographical Texts: Sentence classification (Russian). The corpus contains Wikipedia texts splitted into sentences/ Each sentence has a topic label.

5. Sentiment Labelled Sentences: The dataset contains sentences labelled with positive or negative sentiment.

6. University of Tehran Question Dataset 2016 (UTQD.2016): Persian questions gathered from a jeopardy game broadcasted on Iranian national television.

7. Legal Case Reports: A textual corpus of 4000 legal cases for automatic summarization and citation analysis. For each document we collect catchphrases, citations sentences, citation catchphrases and citation classes.

8. Reuters-21578 Text Categorization Collection: This is a collection of documents that appeared on Reuters newswire in 1987. The documents were assembled and indexed with categories.

9. Sentence Classification: Contains sentences from the abstract and introduction of 30 articles annotated with a modified Argumentative Zones annotation scheme. These articles come from biology, machine learning and psychology.

10. BuddyMove Data Set: User interest information extracted from user reviews published in holidayiq.com about various types of point of interests in South India

11. Travel Reviews: Reviews on destinations in 10 categories mentioned across East Asia. Each traveler rating is mapped as Excellent(4), Very Good(3), Average(2), Poor(1), and Terrible(0) and average rating is used.

12. Tarvel Review Ratings: Google reviews on attractions from 24 categories across Europe are considered. Google user rating ranges from 1 to 5 and average user rating per category is calculated.


Supported By:

 In Collaboration With:

About  ||  Citation Policy  ||  Donation Policy  ||  Contact  ||  CML