Computers have become so common in our daily life, and there has been an increase in demand for Human Computer Interaction. Gesture recognition is an emerging technology for Human Computer Interaction and has a wide variety of applications like gaming and virtual reality. Previous work and methods on finger gesture recognition either use sensors that are worn by users or cameras that require proper light to identify gestures.
Variable importance and interaction measures are crucial to breaking open the "black box” of machine-learned classifiers. The existing metrics, however, are data-driven and lack a solid mathematical foundation, resulting in misleading conclusions on certain types of data. We propose feature power: a new variable importance measure based on the Shapley value of cooperative game theory. We evaluate the validity of this new measure and the behavior of feature power in comparison to existing variable importance metrics.
Time is extremely important to us nowadays because of the fast-paced life and society. However, people still spend substantial time waiting in lines at restaurants. Although some hot applications, for example, Yelp and OpenTable, allow people to make a reservation with restaurants, customers must arrive at the restaurant to sign on a waitlist if the restaurant is full. In that case, a customer has no idea of how many parties ahead of him or how long he needs to wait until he actually arrives.
Twitter spam has been a challenging and critical problem. Previously, researchers have proposed many different machine learning based methods to address this problem. One limitation of those existing solutions is that there is often not enough labeled data. Another issue is feature selection. There is no universal standard on feature selection for spam detection. Researchers often manually choose features based on individual experience and observation.