Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Discovering Fuzzy Classification Rules with Genetic Programming and Co-evolution
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Concept Formation and Decision Tree Induction Using the Genetic Programming Paradigm
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Genetic Programming for Multiple Class Object Detection
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Genetic Programming for data classification: partitioning the search space
Proceedings of the 2004 ACM symposium on Applied computing
Evolving rule-based systems in two medical domains using genetic programming
Artificial Intelligence in Medicine
Genetic programming neural networks: A powerful bioinformatics tool for human genetics
Applied Soft Computing
Genetic programming for epileptic pattern recognition in electroencephalographic signals
Applied Soft Computing
Pareto-coevolutionary genetic programming for problem decomposition in multi-class classification
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Applying genetic programming technique in classification trees
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on intelligent systems for financial engineering and computational finance
Classifier design with feature selection and feature extraction using layered genetic programming
Expert Systems with Applications: An International Journal
Evolving model trees for mining data sets with continuous-valued classes
Expert Systems with Applications: An International Journal
Performance Measures in Classification of Human Communications
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
An autonomous GP-based system for regression and classification problems
Applied Soft Computing
A Comparison of three evolutionary strategies for multiobjective genetic programming
Artificial Intelligence Review
Modifying genetic programming for artificial neural network development for data mining
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
Evolving rule induction algorithms with multi-objective grammar-based genetic programming
Knowledge and Information Systems
Building credit scoring models using genetic programming
Expert Systems with Applications: An International Journal
A comparison of classification accuracy of four genetic programming-evolved intelligent structures
Information Sciences: an International Journal
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
DepthLimited crossover in GP for classifier evolution
Computers in Human Behavior
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Application of genetic programming for multicategory patternclassification
IEEE Transactions on Evolutionary Computation
A novel approach to design classifiers using genetic programming
IEEE Transactions on Evolutionary Computation
Training genetic programming on half a million patterns: an example from anomaly detection
IEEE Transactions on Evolutionary Computation
Artificial Intelligence in Medicine
Engineering Applications of Artificial Intelligence
A space search optimization algorithm with accelerated convergence strategies
Applied Soft Computing
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The important problem of data classification spans numerous real life applications. The classification problem has been tackled by using Genetic Programming in many successful ways. Most approaches focus on classification of only one type of data. However, most of the real-world data contain a mixture of categorical and continuous attributes. In this paper, we present an approach to classify mixed attribute data using Two Layered Genetic Programming (L2GP). The presented approach does not transform data into any other type and combines the properties of arithmetic expressions (using numerical data) and logical expressions (using categorical data). The outer layer contains logical functions and some nodes. These nodes contain the inner layer and are either logical or arithmetic expressions. Logical expressions give their Boolean output to the outer tree. The arithmetic expressions give a real value as their output. Positive real value is considered true and a negative value is considered false. These outputs of inner layers are used to evaluate the outer layer which determines the classification decision. The proposed classification technique has been applied on various heterogeneous data classification problems and found successful.