Determining user-specific hyperparameters for decision support models

A method for determining user-specific hyperparameters for decision support models, the method comprising:

• performing an initial exploration phase by:
• randomly assigning at least one hyperparameter to each user of a plurality of users;
• performing a training phase by:
• analyzing training data, wherein the training data comprises contextual data and a value associated with the at least one randomly assigned hyperparameter;
• and
• determining a relationship between the contextual data and the value associated with the at least one randomly assigned hyperparameter;
• and
• performing an exploration-exploitation phase by:
• dividing the plurality of users into an exploration subset of users and an exploitation subset of users;
• determining at least one optimal hyperparameter for each user of the exploitation subset of users;
• determining, using the at least one optimal hyperparameter, at least one decision support output for each user of the exploitation subset of users;
• randomly assigning at least one hyperparameter to each user of the exploration subset of users;
• and
• determining, using the at least one randomly assigned hyperparameter, at least one decision support output for each user of the exploration subset of users.

A computing device for determining user-specific hyperparameters for decision support models, the computing device comprising:

• a network interface;
• a processor operatively connected to the network interface;
• a memory storing a program comprising instructions that, when executed by the processor, cause the computing device to:
• perform an initial exploration phase by:
• randomly assigning at least one hyperparameter to each user of a plurality of users;
• perform a training phase by:
• analyzing training data, wherein the training data comprises contextual data and a value associated with the at least one randomly assigned hyperparameter;
• and
• determining a relationship between the contextual data and the value associated with the at least one randomly assigned hyperparameter;
• and
• perform an exploration-exploitation phase by:
• dividing the plurality of users into an exploration subset of users and an exploitation subset of users;
• determining at least one optimal hyperparameter for each user of the exploitation subset of users;
• determining, using the at least one optimal hyperparameter, at least one decision support output for each user of the exploitation subset of users;
• randomly assigning at least one hyperparameter to each user of the exploration subset of users;
• and
• determining, using the at least one randomly assigned hyperparameter, at least one decision support output for each user of the exploration subset of users.