Estudi de l'aprenentatge automàtic per a la diagnosi del càncer de mama

Abstract

[en] In this project we will show and discuss the classification algorithms, specifically, for the breast cancer diagnosis. From a theoretical point of view, we will study and prove the basic results of multivariate analysis, such as: dimension theorem, properties of multivariate distributions and the necessary results of Principal Components Analysis (PCA) with their respectively proofs. Then, from a more practical point of view, we will present the observed data, understanding their meaning, studying their properties and the subsequent application of a PCA. Finally, using R programming language, we will apply the data to the classification algorithms Naive Bayes and Support Vector Machine, showing the results that they provide. As well as we will see a brief explanation of the K-NN algorithm.