IDmining-package: IDmining: Intrinsic Dimension for Data Mining

In jeangolay/IDmining: Intrinsic Dimension for Data Mining

Description

Contains techniques for mining large and high-dimensional data sets by using the concept of Intrinsic Dimension (ID). Here the ID is not necessarily an integer. It is extended to fractal dimensions. And the Morisita estimator is used for the ID estimation, but other tools are included as well.

Author(s)

Jean Golay [e-mail] and Mohamed Laib [e-mail],

Maintainer: Jean Golay [e-mail]

References

J. Golay and M. Kanevski (2015). A new estimator of intrinsic dimension based on the multipoint Morisita index, Pattern Recognition 48 (12):4070–4081.

J. Golay, M. Leuenberger and M. Kanevski (2017). Feature selection for regression problems based on the Morisita estimator of intrinsic dimension, Pattern Recognition 70:126–138.

J. Golay and M. Kanevski (2017). Unsupervised feature selection based on the Morisita estimator of intrinsic dimension, Knowledge-Based Systems 135:125-134.

J. Golay, M. Leuenberger and M. Kanevski (2015). Morisita-based feature selection for regression problems. Proceedings of the 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges (Belgium).

See Also

Useful links:

• https://www.sites.google.com/site/jeangolayresearch/

jeangolay/IDmining documentation built on May 6, 2021, 10:49 a.m.