This paper shows the comparison between several well-known
classification algorithms in Machine Learning with the purpose to find
the most suitable algorithm to predict the dwelling time i.e., how long
a certain tourist should stay in a particular tourist spot. This
dwelling time prediction can be adopted for tour and travel agents to
provide optimal scheduling for their package tour. The algorithm in
question is strictly for classification because in this case, the
dwelling time does not require a very specific number of minutes, thus
the time can be classified and restricted into several time frames. The
origin and features of the dataset are described in this paper as well
as the comparison methodology to show the procedure of how the
comparison was made. Lastly, the performance results will be used to
determine which algorithm to use for this specific case and it will be
shown in a form of a graph