Activait

"Activait" is Sirepo's Machine Learning application. Users can upload their own datasets, set their parameters, and run their simulations. All aspects are customizable, from partitioning to training the simulations. Application modes include Regression, Data Analysis, and Classification. Classifier options include K Nearest Neighbors, Decision Tree, Linear SVC, and Logistic Regression. Activait is suitable for any ML simulations and can be adapted to datasets of any size.

Sirepo/Activait Examples (must be registered user to access examples)

• 2019 World Happiness Dataset
• Heart Disease Dataset
• Iris Dataset

U.S. Department of Energy Support

• Sirepo development has been supported by the U.S. Department of Energy Office of Science under multiple awards: By the office of High Energy Physics under Award Nos. DE-SC0011340, DE-SC0015897, and DE-SC0018719. By the office of Basic Energy Sciences under Award Nos. DE-SC0011237, DE-SC0015209, DE-SC0018556, and DE-SC0018571. By the office of Nuclear Physics under Award Nos. DE-SC0015212 and DE-SC0017181. By the office of Advanced Scientific Computing Research under Award Nos. DE-SC0017162 and DE-SC0017057. Sirepo has also been funded in part with Federal funds from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services, under Contract No. 75N91019C00053 and with partial support from RadiaSoft LLC and from Sirepo customers.