A short description The distribution package Related publications Authors & Aknowledgement Contact |

Interpolative Clustering Tree (ICT) is a data mining algorithm that allows us to summarize data sampled over space for a number of goephysical variables by leveraging the power of a spatial-aware clustering algortihm. ICT determines a descriptive and interpolative model of georeferenced data sampled for the set of elds under examination. Data sampled at a specific time are reduced to a cluster model that is also used as interpolation model. Clustering is performed by accounting for the local presence of the spatial autocorrelation property across the sample data. For each cluster, a predictive model of the grouped data is associated to the cluster surface with the e ect of accounting for the relative spatial proximity of the objects that the data refer, smoothing and compacting data in the cluster. These cluster models are used instead of original data to speed-up the interpolation technique without weakening signi cantly its robustness.

Time-evolving Interpolative Clustering Tree (TICT) is a data mining algorithm that resorts to an incremental strategy in order to yield time-evolving ICTs. The model learned at the past time is adapted to the data changes which may turn up in data across the time.

jar |
Description |

ICT | This rar bundle contains (1) ict. jar that allows us to compute Interpolative Clustering Trees (ICT) from the training data of a spatial data collection and use the computed interpolative clusters to predict testing data of this collection;
(2) an example of batch file to run ICT.jar and (3) spatial data collections |

TICT | This rar bundle contains (1) tict. jar that allows us to compute Time-evolving Interpolative Clustering Trees (ICT) from training data of a spatial data stream and use the computed time-evolving interpolative clusters
to predict the testing data of the stream,
(2) an example of batch file to run TICT.jar and (
3) spatial data streams |

Name |
Email address |
Tel. number |
Fax |

Annalisa Appice | annalisa.appice@uniba.it | +39 080 5443262 | +39 080 5443262 |