main main
KEEL - dataset     Multi instance data sets

Multi-Instance data sets represents problems where there is a many-to-one relationship between feature vectors and its output attribute. Usually, the output attribute defines the label of the bag where the instance is located.

When learning a classifier for this kind of data, the classifier should classify a new bag to a determinated class if one (or more) of its associated instances belongs to it.

Each data file has the following structure:

  • @relation: Name of the data set
  • @attribute: Description of an attribute (one for each attribute)
  • @inputs: List with the names of the input attributes
  • @output: Name of the output attribute
  • @data: Starting tag of the data

The first attribute will always be the name of the bag which the instance belongs to. Also, it is required that every instance belonging to a given bag has the same value for its output attribute (its class).

The rest of the file contains all the examples belonging to the data set, expressed in comma sepparated values format.

KEEL - dataset

We offer information about experimental studies using these data sets (result files, papers and more) in the Experimental studies with multi instance data sets section of the repository.


Below you can find all the Multi instance data sets available. For each data set, it is shown its name and its number of examples (instances), attributes (the table details the number of Real/Integer/Nominal attributes in the data) and classes (number of possible values of the output variable). In addition, the table shows if the corresponding data set has missing values or not.

The table allows to download each data set in KEEL format (inside a ZIP file). Additionally, it is possible to obtain the data set already partitioned, by means of a 10-folds cross validation procedure. Finally, we provide a header file to give additional information about each data set and its attributes.

By clicking in the column headers, you can order the table by names (alphabetically), by the number of examples, attributes or classes, or by the presence of missing values. Clicking again will sort the rows in reverse order.

Namedownarrow.png#Attributes (R/I/N)downarrowS.png#Examplesdownarrow.png#Classesdownarrow.pngMiss Val.downarrow.pngData set10-fcvHeader
mutagenesis-atoms11        (10/0/1)16182Nozip.gifzip.giftxt.png
mutagenesis-bonds17        (16/0/1)39952Nozip.gifzip.giftxt.png
eastWest25        (24/0/1)2132Nozip.gifzip.giftxt.png
westEast25        (24/0/1)2132Nozip.gifzip.giftxt.png
mutagenesis-chains25        (24/0/1)53492Nozip.gifzip.giftxt.png
musk1167        (166/0/1)4762Nozip.gifzip.giftxt.png
musk2167        (166/0/1)65982Nozip.gifzip.giftxt.png
tiger231        (230/0/1)12202Nozip.gifzip.giftxt.png
fox231        (230/0/1)13202Nozip.gifzip.giftxt.png
elephant231        (230/0/1)13912Nozip.gifzip.giftxt.png
All data sets (SCV)zip.gif

Collecting Data Sets

If you have some example data sets and you would like to share them with the rest of the research community by means of this page, please be so kind as to send your data to the Webmaster Team with the following information:

  • People answerable for the data (full name, affiliation, e-mail, web page, ...).
  • training and test data sets considered, preferably in ASCII format.
  • A brief description of the application.
  • References where it is used.
  • Results obtained by the methods proposed by the authors or used for comparison.
  • Type of experiment developed.
  • Any additional useful information.

Collecting Results

If you have applied your methods to some of the problems presented here we will be glad of showing your results in this page. Please be so kind as to send the following information to Webmaster Team:

  • Name of the application considered and type of experiment developed.
  • Results obtained by the methods proposed by the authors or used for comparison.
  • References where the results are shown.
  • Any additional useful information.

Contact Us

If you are interested on being informed of each update made in this page or you would like to comment on it, please contact with the Webmaster Team.



 
 Copyright 2004-2015, KEEL (Knowledge Extraction based on Evolutionary Learning)
About the Webmaster Team
Valid XHTML 1.1   Valid CSS!