and the target; or the cost/gain matrix with the correlation coefficient, and so on. More exotic fitness functions that explore model granularity include the area under the ROC curve and rank measure. Also related to this new dimension of classification models, is the idea of assigning probabilities to the model output, which is what is done in logistic regression. Then it is also possible to use these probabilities and evaluate the mean squared error (or some other similar measure) between the probabilities and the actual values, then combine this with the confusion matrix to create very efficient fitness functions for logistic regression. Popular examples of fitness functions based on the probabilities include maximum likelihood estimation and hinge loss. Fitness functions for Boolean problems In logic there is no model structure (as defined above for classification and logistic regression) to explore: the domain and range of logical functions comprises only 0's and 1's or false and true. So, the fitness functions available for Boolean algebra can only be based on the hits or on the confusion matrix as explained in the section above. Selection and elitism Roulette-wheel selection is perhaps the most popular selection scheme used in evolutionary computation. It involves mapping the fitness of each program to a slice of the roulette wheel proportional to its fitness. Then the roulette is spun as many times as there are programs in the population in order to keep the population size constant. So, with roulette-wheel selection programs are selected both according to fitness and the luck of the draw, which means that some times the best traits might be lost. However, by combining roulette-wheel selection with the cloning of the best program of each generation, one guarantees that at least the very best traits are not lost. This technique of cloning the best-of-generation program is known as simple elitism and is used by most stochastic selection schemes. Reproduction with modification The reproduction of programs involves first the selection and then the reproduction of their genomes. Genome modification is not required for reproduction, but without it adaptation and evolution won't take place. Replication and selection The selection operator selects the programs for the replication operator to copy. Depending on the selection scheme, the number of copies one program originates may vary, with some programs getting copied more than once while others are copied just once or not at all. In addition, selection is