# Classification of Imbalanced Travel Mode Choice to Work Data Using Adjustable SVM Model
## 4 Sensitivity Analysis  
Many factors impact the travel mode choice; however, their effects are not the same. Thus, it is necessary to ascertain the magnitude of these impacts and identify the most influential factors on travel mode choice. For this purpose, the authors employed the mutual information (MI) test method [50], which computes the importance of the inputs. MI means a filtering system that captures the random association between inputs and the target. MI examines the dependence among variables and confirms the strength of the connection among them. The MI size among inputs is measured employing the information gain:  
\[Gain(C,D)=Ent(C)-\sum_{h=1}^{H}\frac{\left|C^{h}\right|}{\left|C\right|}Ent \Big{(}C^{h}\Big{)} \tag{15}\]  
where, \(h\) denotes the number of all probable values of \(D\), \(C^{h}\) is the set of \(C\) when \(D\) takes the value \(D_{s}\), and \(Ent(C)\) signifies the information entropy. The larger the value of Gain \((C,D)\), the better the relationship between \(D\) and \(C\).  
Ultimately, the importance magnitude of each attribute for predicting travel mode choice was achieved based on the scores obtained in the MI test. The outcomes of this analysis are shown in Figure 4. The most important attributes were reason for not walking (walkmore), number of drivers in household (drvcnet), and count of adult household  
Figure 3: Models’ performance by each class: (**a**) accuracy (%); (**b**) precision; (**c**) recall, (**d**) F1 score; CLASS 1 = Walk; CLASS 2 = Bicycle; CLASS 3 = Car; CLASS 4 = SUV; CLASS 5 = Van; CLASS 6 = Pickup truck; CLASS 7 = Motorcycle/moped; CLASS 8 = Public or commuter bus; CLASS 9 = Private/charter/tour/shuttle bus.  
\begin{table}
\begin{tabular}{c c} \hline
**Model** & **Accuracy (\%)** \\ \hline [PERSON] and [PERSON] [28] & 83.33 \\ [PERSON] and [PERSON] [27] & 92.99 \\ [PERSON] and [PERSON] [29] & 93.89 \\ [PERSON], [PERSON], [PERSON] and [PERSON] [30] & 90.16 \\ \hline SVM\({}_{\text{AK}}\) & 99.81 \\ \hline \end{tabular}
\end{table}
Table 5: The overall accuracy of SVM-based models and the SVM\({}_{\text{AK}}\) model.  
members at least 18 years old (numadlt). On the other hands, the lowest scores belonged to flexibility of work start time (flextime), owned vehicle longer than a year (vehowned), and gender (r_sex).  
Reasons for not walking among respondents included unsafe street crossings, heavy traffic, and insufficient night lighting. It is clear that any improvement in these street conditions can encourage people to shift from motorized transport to walking. Thus, it makes sense that this factor is among the most influential travel mode choice factors to work [51; 52; 53]. The significance of the number of drivers in households can be attributed to its influence on the usage of vehicles and the generation of more trips. In practice, the likelihood of choosing active transportation options reduces as the number of drivers in a family grows [54]. As the number of adults in a family increases, the need for independent trips rises. Because of the different responsibilities that each adult in the family has, it is not easy to consolidate trips into one trip. This can be easily one of the principal sources of more trip generation and use of motorized transportation.  
The flexibility of work start time was among the least important factors. This could be attributable to work culture of the respondents in the US. However, several previous studies showed that the flexibility of work start time influences the mode choice e.g., [54; 55]. The possession of a vehicle for longer than a year was also an unimportant factor for predicting the choice of travel mode to work. A possible reason for this is that people usually look for flexible and convenient travel options to work. Usually, they are reluctant to replace their private cars with healthy travel modes unless they face new challenges. These challenges can be health problems, heavy traffic, so on. Thus, it is sensible that this factor does not influence the mode choice substantially.