caa a22 4500 467953848 CHVBK 20180323165703.0 cr unu---uuuuu 170328e19900301xx s 000 0 eng 10.1023/A:1022611825350 doi (NATIONALLICENCE)springer-10.1023/A:1022611825350 (NATIONALLICENCE)springer-10.1007/BF00115895 Boolean Feature Discovery in Empirical Learning [Elektronische Daten] [Giulia Pagallo, David Haussler] We investigate the problem of learning Boolean functions with a short DNF representation using decision trees as a concept description language. Unfortunately, Boolean concepts with a short description may not have a small decision tree representation when the tests at the nodes are limited to the primitive attributes. This representational shortcoming may be overcome by using Boolean features at the decision nodes. We present two new methods that adaptively introduce relevant features while learning a decision tree from examples. We show empirically that these methods outperform a standard decision tree algorithm for learning small random DNF functions when the examples are drawn at random from the uniform distribution. Kluwer Academic Publishers, 1990 concept learning nationallicence dynamic bias nationallicence DNF functions nationallicence decision trees nationallicence decision lists nationallicence Pagallo Giulia Department of Computer and Information Sciences, University of California, 95064., Santa Cruz, CA aut Haussler David Department of Computer and Information Sciences, University of California, 95064., Santa Cruz, CA aut Machine Learning Kluwer Academic Publishers-Plenum Publishers 5/1(1990-03-01), 71-99 0885-6125 5:1<71 1990 5 10994 https://doi.org/10.1023/A:1022611825350 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1022611825350 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Pagallo Giulia Department of Computer and Information Sciences, University of California, 95064., Santa Cruz, CA aut NATIONALLICENCE 700 1- Haussler David Department of Computer and Information Sciences, University of California, 95064., Santa Cruz, CA aut NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers-Plenum Publishers 5/1(1990-03-01), 71-99 0885-6125 5:1<71 1990 5 10994 NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00115895 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Bagallo Giulia Department of Computer and Information Sciences, University of California, 95064, Santa Cruz, CA aut NATIONALLICENCE 700 1- Haussler David Department of Computer and Information Sciences, University of California, 95064, Santa Cruz, CA aut NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers 5/1(1990-03-01), 71-99 0885-6125 5:1<71 1990 5 10994 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE NATIONALLICENCE NL-springer