Using Accuracy Analysis to Find the Best Classifier for Intelligent Personal Assistants

An Intelligent Personal Assistant (IPA) is an agent that has the purpose of helping the user with his daily tasks. This paper is focused on IPAs for Internet of Things (IoT) environments. In this sense, a good IPA has the capability of surveying his user behaviour and suggest tasks or make decisions with the intention of simplifying the user interaction with his surroundings. With this in mind, this paper focuses on studying the accuracy of various classifiers, with the objective of finding the one that suits better the needs of an IPA for IoT. The aim is to test each algorithm with a dataset of events, that relate to past behaviours of the user, and find if there is an opportunity to notify the user that he/she may want to take an action or create an automation based on the learned behaviour.