  In this paper, we propose a feature pioneering method using Large Language
Models (LLMs). In the proposed method, we use Chat-GPT 1 to find new sensor
locations and new features. Then we evaluate the machine learning model which
uses the found features using Opportunity Dataset [ 4 , 9]. In current machine
learning, humans make features, for this engineers visit real sites and have
discussions with experts and veteran workers. However, this method has the
problem that the quality of the features depends on the engineer. In order to
solve this problem, we propose a way to make new features using LLMs. As a
result, we obtain almost the same level of accuracy as the proposed model which
used fewer sensors and the model uses all sensors in the dataset. This
indicates that the proposed method is able to extract important features
efficiently.
