Data increment and enrichment for training machine learning based energy prediction model
Description
This dataset is used for training of component based machine learning (CBML) models described in the linked article. The article examines the effect of increasing and enriching training data on machine learning model's ability to generalise. Please read the full article for the relevant details of ML models. There are seven training dataset BaseCase, E-1, E-2, E-3, I-1, I-2, and I-3 and one test dataset TestData. The trained ML components are saved under Models folder in each dataset. The performance.csv file describes the performance of ML components trained on the separate training dataset.
Files
Steps to reproduce
Run the program "Programs/RunDLAnalysis.py" using a python program. The tool will generate the ML models and make prediction on the test dataset. The actual energy predictions and predicted energy predication can be used to obtain the relevant performances of the ML models.
Institutions
- Katholieke Universiteit Leuven