Análisis de las características de los tipos de algoritmos de clustering en el aprendizaje no supervisado.
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 i...
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| フォーマット: | bachelorThesis |
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2022
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| オンライン･アクセス: | http://dspace.utb.edu.ec/handle/49000/11594 |
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タグ追加 | 要約: | 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. |
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