- author = "Francesco Archetti and Mauro Castelli and Ilaria Giordani and Leonardo Vanneschi",
- title = "Classification of colon tumor tissues using genetic programming",
- booktitle = "Artificial Life and Evolutionary Computation: Proceedings of Wivace 2008",
- year = "2008",
- editor = "J. Roberto Serra and Marco Villani and Irene Poli",
- pages = "49--58",
- address = "Venice, Italy",
- month = "8-10 " # sep,
- publisher = "World Scientific Publishing Co.",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "9789814287456",
-
URL = "
ftp://ftp.ce.unipr.it/pub/cagnoni/WIV08/paper%202.pdf",
- broken = "http://ebooks.worldscinet.com/ISBN/9789814287456/9789814287456_0004.html",
- size = "10 pages",
- abstract = "A Genetic Programming (GP) framework for classification is presented in this paper and applied to a publicly available biomedical microarray dataset representing a collection of expression measurements from colon biopsy experiments [3]. We report experimental results obtained using two different well known fitness criteria: the area under the receiving operating curve (ROC) and the percentage of correctly classified instances (CCI). These results, and their comparison with the ones obtained by three non-evolutionary Machine Learning methods (Support Vector Machines, Voted Perceptron and Random Forests) on the same data, seem to hint that GP is a promising technique for this kind of classification both from the viewpoint of the accuracy of the proposed solutions and of the generalisation ability. These results are encouraging and should pave the way to a deeper study of GP for classification applied to biomedical microarray data sets.",
-
notes = "Workshop Italiano di Vita Artificiale e Computazione
Evolutiva http://wivace.unimore.it/
Dept. of Informatics, Systems and Communication, University of Milano-Bicocca, 20126 Milan, Italy
http://microarray.princeton.edu/oncology/affydata/index.html",
