A Practical Demonstration of GP-Based Software

3 Machine Learning Methods in Chemoinformatics for Drug Discovery 

The error metric is a measure of a model s prediction accuracy. The software provides a number of error metrics such as squared error, worst-case error, logarithm error, median error, interquartile absolute error and signed difference for minimization. Additionally, options to maximize the correlation coefficient or the B goodness of fit or experimental hybrid that considers both absolute error and correlation are also available. Data sphtting is an important step which divides the data into a training set to generate solutions and a test set to check the accuracy of those solutions (Fig. 3.62). 

The search is initialized by clicking on the run button a log file is created simultaneously to monitor the performance and progress of the ongoing search. The results show the best solutions that have been obtained. The best solutions are 

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