Análisis comparativo de algoritmos de árboles de decisión en el procesamiento de datos biológicos

in this work the performance of several algorithms of decision trees is evaluated, to find through comparisons, which are more effective in the analysis of biological data. Decision trees are a classification model used in artificial intelligence, whose main feature is its visual contribution to decision making. To test the performance in the classification process of the decision trees, biological data of real patients will be used, this data will be analyzed in the software WEKA. With this comparison, what is also sought is to determine the relevance of decision trees, is whether they can be a good tool for medical diagnostics. These comparisons will lead us to clarify which algorithm is the most efficient and appropriate for the analysis of said data, and thus arrive at a good conclusion.