@InProceedings{RochaPapaMeir:2010:HoFaYo,
author = "Rocha, Anderson and Papa, Jo{\~a}o Paulo and Meira, Luis A. A.",
affiliation = "Institute of Computing, University of Campinas (UNICAMP), Brazil
and Department of Computer Science, State University of S{\~a}o
Paulo (UNESP), Brazil and Department of Science and Technology,
Federal University of S{\~a}o Paulo (UNIFESP), Brazil",
title = "How Far You Can Get Using Machine Learning Black-Boxes",
booktitle = "Proceedings...",
year = "2010",
editor = "Bellon, Olga and Esperan{\c{c}}a, Claudio",
organization = "Conference on Graphics, Patterns and Images, 23. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "Learning Black-Boxes, Metrics Space, Pattern Analysis, Support
Vector Machines, Optimum-Path Forest, Neural Networks, K-Nearest
Neighbors.",
abstract = "Supervised Learning (SL) is a machine learning research area which
aims at developing techniques able to take advantage from labeled
training samples to make decisions over unseen examples. Recently,
a lot of tools have been presented in order to perform machine
learning in a more straightfor- ward and transparent manner.
However, one problem that is increasingly present in most of the
SL problems being solved is that, sometimes, researchers do not
completely understand what supervised learning is and, more often
than not, publish results using machine learning black-boxes. In
this paper, we shed light over the use of machine learning
black-boxes and show researchers how far they can get using these
out-of-the- box solutions instead of going deeper into the
machinery of the classifiers. Here, we focus on one aspect of
classifiers namely the way they compare examples in the feature
space and show how a simple knowledge about the classifiers
machinery can lift the results way beyond out-of-the-box machine
learning solutions.",
conference-location = "Gramado, RS, Brazil",
conference-year = "30 Aug.-3 Sep. 2010",
doi = "10.1109/SIBGRAPI.2010.34",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2010.34",
language = "en",
ibi = "8JMKD3MGPBW34M/386A2NP",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/386A2NP",
targetfile = "rocha-et-al-sibgrapi-2010-camera-ready.pdf",
urlaccessdate = "2024, Apr. 28"
}