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In this project, the objective is to predict the electricity consumption in Watt-hours of a Belgian low energy house. The explanatory variables are temperature and humidity measurements from sensors in the house, as well as weather data from a nearby station and the global consumption of the country.

License: GNU General Public License v3.0

Jupyter Notebook 99.97% Python 0.03%

houseelectricityprediction's Introduction

HouseElectricityPrediction

Authors : Sivane Marciano - Oumane Seydina Niang - Yanis Fellah - Lounes Guergous - Marvin Tordjamn - Sajjad Mahdavi

In this project, the objective is to predict the electricity consumption in Watt-hours of a Belgian low energy house. The explanatory variables are temperature and humidity measurements from sensors in the house, as well as weather data from a nearby station and the global consumption of the country.

Getting started

Install

To run a submission and the notebook you will need the dependencies listed in requirements.txt. You can install the dependencies with the following command-line:

pip install -U -r requirements.txt

If you are using conda, we provide an environment.yml file for similar usage.

Challenge description

Get started with the dedicated notebook. It contains the following:

Table of Contents
  1. Problem statement

  2. Data Exploration

  • Features Explanation
  • Features Exploration
  1. Data pre-processing
  • Categorical Features
  • Missing Values
  1. Workflow

  2. Submission details

  3. RAMP submission

Test a submission

The submissions need to be located in the submissions folder. For instance for my_submission, it should be located in submissions/my_submission.

To run a specific submission, you can use the ramp-test command line:

ramp-test --submission my_submission

You can get more information regarding this command line:

ramp-test --help

To go further

You can find more information regarding ramp-workflow in the dedicated documentation

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