https://github.com/maximilian-janisch/2020-UZH-Random-Forests

Repository for the final project of the course An Introduction to Machine Learning by Marco and Maximilian
https://github.com/maximilian-janisch/2020-UZH-Random-Forests

Last synced: about 1 month ago
JSON representation

Repository for the final project of the course An Introduction to Machine Learning by Marco and Maximilian

• Host: GitHub
• URL: https://github.com/maximilian-janisch/2020-UZH-Random-Forests
• Owner: maximilian-janisch
• Created: 2020-01-05T16:25:09.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-01-18T18:38:55.000Z (almost 5 years ago)
• Last Synced: 2023-08-04T17:27:54.638Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 9.18 MB
• Stars: 6
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome - maximilian-janisch/2020-UZH-Random-Forests - Repository for the final project of the course An Introduction to Machine Learning by Marco and Maximilian (Jupyter Notebook)
• awesome - maximilian-janisch/2020-UZH-Random-Forests - Repository for the final project of the course An Introduction to Machine Learning by Marco and Maximilian (Jupyter Notebook)

README

        
# Sustainable-Forest-Of-Codes

## Short Description

This repository contains an implementation of the [Random Forest algorithm for classification](https://en.wikipedia.org/wiki/Random_forest). This algorithm is then applied to an artifically generated dataset about e-scooters. Also, the performance of the algorithm is compared to that of other common classification algorithms from the sklearn library.

This repository was created for a project of the 2019/2020 course [*An Introduction to Machine Learning*](https://www.math.uzh.ch/index.php?id=ve_vo_det&key2=3699&semId=39) at the math department of the University of Zurich.

### How to run the code

Install Python 3.7 or newer from https://www.python.org/. Download all the files in this repository and put them in a dedicated directory. In order to use the IPython Notebook you will have to install [Jupyter](https://jupyter.org/install). Make sure to have all requirements installed, for example by using `pip install -r requirements.txt`.

## Group members:

* Marco Bertenghi

* Maximilian Janisch

### Todo:

* ~~Test section~~

* ~~**Text for grid search**~~

* ~~**Text for explaratory Data Analysis**~~

* ~~Grid search~~

* **Copy the code from the RandomForestImplementation folder into the Maximilian-Marco Notebook**

* Warnings ?