Machine Learning for the Evolutionary Analysis of Breast Cancer

The use of machine learning allows the creation of a predictive data model, as a result of the analysis in a data set with 286 instances and nine attributes belonging to the Institute of Oncology of the University Medical Center. Ljubljana. Based on this situation, the data are preprocessed by applying intelligent data analysis techniques to eliminate missing values as well as the evaluation of each attribute that allows the optimization of results. We used several classification algorithms including J48 trees, random forest, bayes net, naive bayes, decision table, in order to obtain one that given the characteristics of the data, would allow the best classification percentage and therefore a better matrix of confusion, Using 66 % of the data for learning and 33 % for validating the model. Using this model, a predictor with a 71,134 % e effectiveness is obtained to estimate or not the recurrence of breast cancer.