@article { , title = {Feature construction and selection using genetic programming and a genetic algorithm}, 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 using the C4.5 decision tree learning algorithm. The Genetic Programming is used to construct new features from those available in the data, a potentially significant process for data mining since it gives consideration to hidden relationships between features. The Genetic Algorithm is used to determine which such features are the most predictive. Using ten well-known datasets we show that our approach, in comparison to C4.5 alone, provides marked improvement in a number of cases.}, doi = {10.1007/3-540-36599-0\_21}, eissn = {1611-3349}, isbn = {354000971X; 9783540009719}, issn = {0302-9743}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, pages = {229-237}, publicationstatus = {Published}, publisher = {Springer Verlag}, url = {https://uwe-repository.worktribe.com/output/1074750}, volume = {2610}, keyword = {Unconventional Computing Group, Computer Science Research Centre, programming techniques, computation by abstract devices, algorithm analysis and problem complexity, artificial intelligence, pattern recognition, bioinformatics}, year = {2003}, author = {Smith, Matthew G. and Bull, Larry} editor = {Ryan, Conor and Soule, Terence and Keijzer, Maarten and Tsang, Edward and Poli, Riccardo and Costa, Ernesto} }