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http://hdl.handle.net/10609/90987
Title: | Predictor para el síndrome de Lynch: comparativa y análisis de algoritmos de machine learning |
Author: | Muñoz López, Marta |
Tutor: | Andrio, Pau |
Abstract: | Along the development of this project, Lynch Syndrome has been analysed, an hereditarian syndrome which increases the possibilities of suffering different kinds of cancer. This syndrome is detected due to mutations in different genes like: MLH1, MSH1, MSH2, MSH6 o PMS2. A predictor has been developed coming from individual characteristics. First of all, data have been collected in order to apply to different machine learning algorithms. After finding the most suitable data, an analysis has been done. After that, different classification algorithms have been studied with the purpose of comparing all of them. The main library used in the product development has been Python scikit-learn. Some algorithms have been searched of in detail to obtain optima results. The project has been determined because of a small sample data. |
Keywords: | Lynch syndrome scikits.learn Python machine learning |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Sep-2018 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
Files in This Item:
File | Description | Size | Format | |
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mmunozlopez2TFM0119memoria.pdf | Memoria del TFM | 1,07 MB | Adobe PDF | View/Open |
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