This project evaluates the impact of alternative measures on dynamic predictor selection performance to predict one-step-ahead microservices time series.
$ virtualenv venv
$ source venv/bin/activate
$ pip3 install -r requirements.txt
$ apt install zip -y; unzip pickle.zip;
Summary of the main repository files.
Files | Content description |
---|---|
series-descriptions.csv | Description of the datasets. |
result | MSE restults. |
pickle | Trained models saved in .pickle |
File | File description |
---|---|
competences.py | Competence measures. |
dynamic_selection.py | Run the DS dynamic selection algorithm. |
results.py | Generates csv results from models. |
generate_oracle.py | Generate results from Oracle. |
similarities.py | Similarity measures. |
train_models.py | Train monolithic models and the homogeneous pool. |