Análisis de las características de los tipos de algoritmos de clustering en el aprendizaje no supervisado.
| dc.contributor.advisor | Mejía Viteri, José Teodoro | |
| dc.contributor.author | Choez Franco, Ángel Steven | |
| dc.date.accessioned | 2022-05-16T15:27:55Z | |
| dc.date.available | 2022-05-16T15:27:55Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | http://dspace.utb.edu.ec/handle/49000/11594 | |
| dc.description | In recent years, technological advances have led to the generation of large volumes of data, and one of the problems is the time to classify and extract data, so unsupervised learning plays a fundamental role in the process using the types of clustring algorithms. Therefore, the present case study is based on performing an "analysis of the characteristics of the types of clustering algorithms in unsupervised learning", whose objective is to analyze the characteristics of the types of clustering algorithms since these algorithms are based on the assumption that patterns can be grouped according to their similarity. That is, it performs a process to explore and analyze the data where the structure they have is unknown, whose purpose of finding patterns in the data that form groups with similar characteristics. | es_ES |
| dc.description | In recent years, technological advances have led to the generation of large volumes of data, and one of the problems is the time to classify and extract data, so unsupervised learning plays a fundamental role in the process using the types of clustring algorithms. Therefore, the present case study is based on performing an "analysis of the characteristics of the types of clustering algorithms in unsupervised learning", whose objective is to analyze the characteristics of the types of clustering algorithms since these algorithms are based on the assumption that patterns can be grouped according to their similarity. That is, it performs a process to explore and analyze the data where the structure they have is unknown, whose purpose of finding patterns in the data that form groups with similar characteristics. | es_ES |
| dc.description.abstract | En los últimos años, los avances tecnológicos han llevado a la generación de grandes volúmenes de datos, y uno de los problemas es la hora de clasificar y extraer datos, por ello el aprendizaje no supervisado juega un papel fundamental en el proceso utilizando los tipos de algoritmos de clustring. Por ello el presente estudio de caso, se basa en realizar un “análisis de las características de los tipos de algoritmos de clustering en el aprendizaje no supervisado”, cuyo objetivo es analizar las características de los tipos de algoritmos de clustering ya que estos algoritmos se basan en la suposición de que los patrones se pueden agrupar en función de su similitud. Es decir que realiza un proceso para explorar y analizar los datos donde se desconoce la estructura que tienen, cuya finalidad es encontrar patrones en los datos que formen grupos con características similares. | es_ES |
| dc.format.extent | 35 p. | es_ES |
| dc.language.iso | es | es_ES |
| dc.publisher | Babahoyo: UTB-FAFI. 2022 | es_ES |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Ecuador | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ec/ | * |
| dc.subject | Clustering | es_ES |
| dc.subject | Análisis | es_ES |
| dc.subject | Patrones de datos | es_ES |
| dc.title | Análisis de las características de los tipos de algoritmos de clustering en el aprendizaje no supervisado. | es_ES |
| dc.type | bachelorThesis | es_ES |
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