/tesiTriennale

codice utilizzato per effettuare lo studio proposto nella tesi

Primary LanguagePython

Riconoscimento di flussi di mobilità urbana con modelli Gradient Boosting

Bachelor degree's thesis work produced by Pietro Tempesti

Objective of this work is the comparison of the results obtained by many ML ensamble models in classification on a dataset regarding the urban mobility of Istanbul.

You can find all the results in the documentation provided in this repository (in Italian), and you can run the Python code used to perform analysis over the Gradient Boosting algorithms.

Installation and running

You have to download the repository and run the main.py file: you can choose which model you want to use to perform the classification.