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Appliance Energy Prediction

Capstone project for Udacity Machine Learning Nanodegree

Early Work

Dataset Link

Dataset Information

  • Number of instances: 19,735
  • Number of attributes: 29

Attribute Information

  1. date: year-month-day hour:minute:second
  2. T1: Temperature in kitchen area, in Celsius
  3. RH_1: Humidity in kitchen area, in %
  4. T2: Temperature in living room area, in Celsius
  5. RH_2: Humidity in living room area, in %
  6. T3: Temperature in laundry room area
  7. RH_3: Humidity in laundry room area, in %
  8. T4: Temperature in office room, in Celsius
  9. RH_4: Humidity in office room, in %
  10. T5: Temperature in bathroom, in Celsius
  11. RH_5: Humidity in bathroom, in %
  12. T6: Temperature outside the building (north side), in Celsius
  13. RH_6: Humidity outside the building (north side), in %
  14. T7: Temperature in ironing room, in Celsius
  15. RH_7: Humidity in ironing room, in %
  16. T8: Temperature in teenager room 2, in Celsius
  17. RH_8: Humidity in teenager room 2, in %
  18. T9: Temperature in parents’ room, in Celsius
  19. RH_9: Humidity in parents’ room, in %
  20. T_out: Temperature outside (from Chievres weather station), in Celsius
  21. Pressure: (from Chievres weather station), in mm Hg
  22. RH_out: Humidity outside (from Chievres weather station), in %
  23. Wind speed: (from Chievres weather station), in m/s
  24. Visibility: (from Chievres weather station), in km
  25. T_dewpoint: (from Chievres weather station), °C
  26. rv1: Random variable 1, non-dimensional
  27. rv2: Random variable 2, non-dimensional
  28. Lights: energy use of light fixtures in the house in Wh
  29. Appliances: energy use in Wh (Target Variable)

Software Requirements

Python version: 3.5

The software requirements are mentioned in the requirements.txt file in top level directory. To install these dependencies, use the command:-

pip3 install -r requirements.txt


The installation of SciPy would fail on Windows because of absence of Numpy + MKL. To install dependencies on windows, follows the steps:-
  1. Download NumPy + MKL for the mentioned python version from here.
  2. Remove the Numpy's entry from requirements.txt.
  3. Run the command: pip3 install -r requirements.txt.

Running the software

To run the software, navigate to the top level directory and type

jupyter notebook predict_energy_consumption.ipynb