Genetic Programming for Improved Receiver Operating Characteristics

Genetic programming (GP) can automatically fuse given classifiers of diverse types to produce a combined classifier whose Receiver Operating Characteristics (ROC) are better than [Scott et al.1998b]'s "Maximum Realisable Receiver Operating Characteristics" (MRROC). I.e. better than their convex hull. This is demonstrated on a satellite image processing bench mark using Naive Bayes, Decision Trees (C4.5) and Clementine artificial neural networks.

[1]  William B. Langdon,et al.  Size fair and homologous tree genetic programming crossovers , 1999 .

[2]  William B. Langdon Data structures and genetic programming , 1995 .

[3]  Thomas G. Dietterich What is machine learning? , 2020, Archives of Disease in Childhood.

[4]  Ron Kohavi,et al.  MLC++: a machine learning library in C++ , 1994, Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94.

[5]  Terence Soule,et al.  Voting teams: a cooperative approach to non-typical problems using genetic programming , 1999 .

[6]  William J. Christmas,et al.  Combining multiple experts for classifying shot changes in video sequences , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[7]  Mahesan Niranjan,et al.  Realisable Classifiers: Improving Operating Performance on Variable Cost Problems , 1998, BMVC.

[8]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[9]  orgTom Fawcett fawcett Robust Classiication for Imprecise Environments , 1989 .

[10]  B. Buxtong Genetic Programming for Combining Classiiers , 2001 .

[11]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[12]  Brian D. Ripley,et al.  Pattern Recognition and Neural Networks , 1996 .

[13]  William B. Langdon,et al.  Evolving Receiver Operating Characteristics for Data Fusion , 2001, EuroGP.

[14]  Ron Kohavi,et al.  Wrappers for Feature Subset Selection , 1997, Artif. Intell..

[15]  Mahesan Niranjan,et al.  Parcel: Feature Subset Selection in Variable Cost Domains , 1998 .

[16]  Geoffrey E. Hinton,et al.  Adaptive Mixtures of Local Experts , 1991, Neural Computation.

[17]  William B. Langdon,et al.  Genetic programming for combining classifiers , 2001 .

[18]  J A Swets,et al.  Better decisions through science. , 2000, Scientific American.