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PRAIg '16 / +pics

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AERFAI Summer School on Deep Learning

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Alicante July 5-6, 2017

10th international workshop on Machine Learning and Music

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Barcelona: 16th October 2017

Publications:

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  1. Calvo-Zaragoza, J.; Valero-Mas, J.J.; Rico-Juan, J.R.
    "Prototype Generation on Structural Data using Dissimilarity Space Representation: A Case of Study"
    7th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), ISBN: 978-3-319-19389-2, pp. 72-82, Santiago de Compostela, Spain (2015)
    : bibtex : pdf
    Abstract:

    Data Reduction techniques are commonly applied in instance-based classification tasks to lower the amount of data to be processed. Prototype Selection (PS) and Prototype Generation (PG) constitute the most representative approaches. These two families differ in the way of obtaining the reduced set out of the initial one: while the former aims at selecting the most representative elements from the set, the latter creates new data out of it. Although PG is considered to better delimit decision boundaries, operations required are not so well defined in scenarios involving structural data such as strings, trees or graphs. This work proposes a case of study with the use of the common RandomC algorithm for mapping the initial structural data to a Dissimilarity Space (DS) representation, thereby allowing the use of PG methods. A comparative experiment over string data is carried out in which our proposal is faced to PS methods on the original space. Results show that PG combined with RandomC mapping achieves a very competitive performance, although the obtained accuracy seems to be bounded by the representativity of the DS method.

@inproceedings {
 author = "Calvo-Zaragoza, J.; Valero-Mas, J.J.; Rico-Juan, J.R.",
 title  = "Prototype Generation on Structural Data using Dissimilarity Space Representation: A Case of Study",
 address = "Santiago de Compostela, Spain",
 booktitle = "7th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)",
 editor = "Paredes, Roberto and Cardoso, Jaime S. and Pardo, Xosé M.",
 isbn = "978-3-319-19389-2",
 month = "June",
 pages = "72-82",
 publisher = "Springer",
 year = "2015"
}
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