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PCA, Clustering, LDA y PLS Regression aplicado a estadísticas de partidas reales de Fortnite.

machine-learning partial-least-squares-regression k-means-clustering linear-discriminant-analysis principle-component-analysis r

machine-learning-with-fortninte-data's Introduction

Aplicando machine learning a estadísticas reales de un juego multijugador.

Es un proyecto hecho para la asignatura Modelos Predictivos y Descriptivos I del Grado en Ciencia de Datos de la UPV. Aplicamos varias técnicas de Machine Learning como PCA, clustering, LDA o PLS regression para comprender los datos extraídos de numerosas partidas en el juego multijugador Fortnite. Gracias al uso de estos métodos se ha logrado comprender como las distintas formas con las que se puede interactuar con el juego afectan al resultado final que se obtiene y a predecir por la forma de jugar de un usuario si esta bajo los efectos del cannabis. Todo el código está escrito en R y las diferentes librerías que se utilizan se pudene ver dentro del r-markdown.

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