%0 Conference Paper %1 1277291 %A Smith, Matthew %A Bull, Larry %B GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation %C London %D 2007 %E Thierens, Dirk %E Beyer, Hans-Georg %E Bongard, Josh %E Branke, Jurgen %E Clark, John Andrew %E Cliff, Dave %E Congdon, Clare Bates %E Deb, Kalyanmoy %E Doerr, Benjamin %E Kovacs, Tim %E Kumar, Sanjeev %E Miller, Julian F. %E Moore, Jason %E Neumann, Frank %E Pelikan, Martin %E Poli, Riccardo %E Sastry, Kumara %E Stanley, Kenneth Owen %E Stutzle, Thomas %E Watson, Richard A %E Wegener, Ingo %I ACM Press %K algorithms, construction, discovery, factors, feature genetic human knowledge parsimony, post-processing programming, readability, selection, %P 1694--1701 %T Improving the human readability of features constructed by genetic programming %U http://doi.acm.org/10.1145/1276958.1277291 %V 2 %X The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is classified by an external classifier. Genetic Programming is combined with a Genetic Algorithm to construct and select new features from those available in the data, a potentially significant process for data mining since it gives consideration to hidden relationships between features. We then examine techniques to improve the human readability of these new features and extract more information about the domain.

@inproceedings{1277291, abstract = {The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is classified by an external classifier. Genetic Programming is combined with a Genetic Algorithm to construct and select new features from those available in the data, a potentially significant process for data mining since it gives consideration to hidden relationships between features. We then examine techniques to improve the human readability of these new features and extract more information about the domain.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {London}, author = {Smith, Matthew and Bull, Larry}, biburl = {https://www.bibsonomy.org/bibtex/2ed4ff1bb5427ec9aee98f81ef7d4b523/brazovayeye}, booktitle = {GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation}, editor = {Thierens, Dirk and Beyer, Hans-Georg and Bongard, Josh and Branke, Jurgen and Clark, John Andrew and Cliff, Dave and Congdon, Clare Bates and Deb, Kalyanmoy and Doerr, Benjamin and Kovacs, Tim and Kumar, Sanjeev and Miller, Julian F. and Moore, Jason and Neumann, Frank and Pelikan, Martin and Poli, Riccardo and Sastry, Kumara and Stanley, Kenneth Owen and Stutzle, Thomas and Watson, Richard A and Wegener, Ingo}, interhash = {1d64017c5489f340e3aff72120f82d04}, intrahash = {ed4ff1bb5427ec9aee98f81ef7d4b523}, isbn13 = {978-1-59593-697-4}, keywords = {algorithms, construction, discovery, factors, feature genetic human knowledge parsimony, post-processing programming, readability, selection,}, month = {7-11 July}, notes = {GECCO-2007 A joint meeting of the sixteenth international conference on genetic algorithms (ICGA-2007) and the twelfth annual genetic programming conference (GP-2007). ACM Order Number 910071}, organisation = {ACM SIGEVO (formerly ISGEC)}, pages = {1694--1701}, publisher = {ACM Press}, publisher_address = {New York, NY, USA}, timestamp = {2008-06-19T17:51:51.000+0200}, title = {Improving the human readability of features constructed by genetic programming}, url = {http://doi.acm.org/10.1145/1276958.1277291}, volume = 2, year = 2007 }