Creación de un Árbol de Decisión para la Predicción de Tonos a Partir de un Data Set

Víctor Manuel Vilca Rojas; Aldair Bryan Salcedo Chávez; Jairo Miguel Castillo Rojas; Valery Byrne Macias

doi:10.48168/innosoft.s11.a85

Víctor Manuel Vilca Rojas National University of Saint Augustine https://orcid.org/0000-0002-6193-8057
Aldair Bryan Salcedo Chávez National University of Saint Augustine
Jairo Miguel Castillo Rojas National University of Saint Augustine
Valery Byrne Macias National University of Saint Augustine

DOI: 10.48168/innosoft.s11.a85

PURL: 42411/s11/a85

ARK: ark:/42411/s11/a85

Keywords: Artificial intelligence, decision tree, music analysis, pitch detection, music

Abstract

Musical analysis is a process that has been carried out for years where different experts have sought to study various musical pieces. This process begins with the learning of tone, note and chord detection, where students have to train their ears to be able to carry it out. In this context, in the following work a decision tree has been made based on a dataset of Bach choirs in order to predict chords from tones. The dataset was divided into 80% to create the tree and 20% for testing, then the data transformation was performed to perform an analysis of the data, with this a decision tree was finally created with a depth of 15 and an accuracy of 75.52%, the tests were finally carried out and we found good results for the accuracy of the tree.

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