A technological revolution has emerged in the context of mobility surveys with the widescale usability of wearable and onboard global positioning system (GPS) devices. Sri Lanka is also at the edge of utilizing these, in replacing the traditional methods. The earnestness' for this transition is supported by the deficiencies such as higher cost, higher nonresponses rates, over and under-reporting, and small sample sizes of traditional surveys. The activity that a passenger performs after a trip, or the purpose of a trip is a vital concern in transportation research as it is the reason behind the generation of travel demands. Hence, trip purpose inference from GPS data has become an important study area in this context [1]. Gong et al. [2] reviewing the existing trip purpose inference studies categorized the methodologies that had been used into three as rule-based, probabilistic, and machine learning-based. In this study, we utilized the GPS records of taxi trips from a popular service provider in the country as shown in Figure 1 in developing a suitable trip purpose inference approach.