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meta-data     (Machine Learning Data)

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Metadata

NameMeta-data
Data typesMultivariate
Data taskClassification
Attribute typesCategorical, Integer, Real
Instances528
Attributes22
Year1996
AreaOther
DescriptionMeta-Data was used in order to give advice about which classification method is appropriate for a particular dataset (taken from results of Statlog project).

Citing the repository in published materials

If you find Network Repository useful for your research, please consider citing the following paper:

@inproceedings{nr,
     title={The Network Data Repository with Interactive Graph Analytics and Visualization},
     author={Ryan A. Rossi and Nesreen K. Ahmed},
     booktitle={Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},
     url={http://networkrepository.com},
     year={2015}
}

Note that if you transform/preprocess this data for your own research, we ask that you please share the data by uploading it along with details on the transformation and reference to any published materials.

@     Name = Meta-dataData types = MultivariateData task = ClassificationAttribute types = Categorical,
Integer,      RealInstances = 528Attributes = 22Year = 1996Area = OtherDescription = Meta-Data was used in order to give advice about which classification method is appropriate for a particular dataset (taken from results of Statlog project).,

Interactive Visualization of Node-level Properties and Statistics

Tools for Interactive Exploration of Node-level Statistics

Visualize and interactively explore meta-data and its important node-level statistics!

  • Each point represents a node (vertex) in the graph.
  • A subset of interesting nodes may be selected and their properties may be visualized across all node-level statistics. To select a subset of nodes, hold down the left mouse button while dragging the mouse in any direction until the nodes of interest are highlighted.This feature allows users to explore and analyze various subsets of nodes and their important interesting statistics and properties to gain insights into the graph data
  • Zoom in/out on the visualization you created at any point by using the buttons below on the left.
  • Once a subset of interesting nodes are selected, the user may further analyze by selecting and drilling down on any of the interesting properties using the left menu below.
  • We also have tools for interactively visualizing, comparing, and exploring the graph-level properties and statistics.
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