## 4 Experiments (Application to [PERSON]'s Airline Passenger Satisfaction Data) and Discussion
\begin{table}
\begin{tabular}{l} \hline
**No.** **Fuzzy Classification Rules** \\ \hline
**Solution No. 6** (\(ACC^{(lrn)}=86.6\%\), \(ACC^{(lst)}=86.4\%\)): \\
1–5. _These rules are the same as rules Nos. 1–5 from Solution No. 5_. \\
6. _This rule is an extension of rule No. 6 from Solution No. 5_: \\
**IF** Inflight WiFi service is low or medium **AND** Type of travel is personal travel **AND** Flight distance is short **AND** Customer type is loyal customer **THEN** \\ Passenger is neutral or dissatisfied \\
7–8. _These rules are the same as rules Nos. 7–8 from Solution No. 5_. \\
9. **IF** Inflight WiFi service is low or medium **AND** Flight distance is short **AND** Customer type is disdisalyal customer **THEN** Passenger is neutral or dissatisfied \\
10. **IF** Inflight WiFi service is low or medium **AND** Customer type is loyal customer **AND** Ease of online booking is high **AND** Leg room service is high **THEN** Passenger is satisfied \\
11. **IF** Inflight WiFi service is low or medium **AND** Type of travel is personal travel **AND** Leg room service is low or medium **THEN** Passenger is neutral or dissatisfied \\ \hline
**Solution No. 7** (\(ACC^{(lrn)}=88.3\%\), \(ACC^{(lst)}=88.1\%\)): \\
1–5. _These rules are the same as rules Nos. 1–5 from Solution No. 6_. \\
6. _This rule is an extension of rule No. 6 from Solution No. 4_: \\
**IF** Inflight WiFi service is low or medium **AND** Type of travel is personal travel **AND** Ease of online booking is no\_answer or low **THEN** Passenger is neutral or dissatisfied \\
7–9. _These rules are the same as rules Nos. 7–9 from Solution No. 6_. \\
10. _This rule is an extension of rule No. 1 from Solution No. 1_: \\
**IF** Inflight entertainment is no\_answer or low **AND** Seat comfort is no\_answer **THEN** Passenger is satisfied \\
11. _This rule is an extension of rule No. 6 from Solution No. 4_: \\
**IF** Inflight WiFi service is low or medium **AND** Type of travel is personal travel **AND** Ease of online booking is medium **THEN** Passenger is neutral or dissatisfied \\
12. **IF** Inflight WiFi service is no\_answer **AND** Ease of online booking is no\_answer or low **THEN** Passenger is satisfied \\
13. **IF** On-board service is no\_answer or low **AND** Seat comfort is no\_answer **THEN** Passenger is satisfied \\
14. **IF** On-board service is no\_answer or low **AND** Seat comfort is low or medium **THEN** Passenger is neutral or dissatisfied \\
15. **IF** On-board service is medium **AND** Leg room service is no\_answer **THEN** Passenger is satisfied \\
16. **IF** On-board service is high **AND** Ease of online booking is high **AND** Leg room service is high **THEN** Passenger is satisfied \\
17. **IF** Seat comfort is low or medium **AND** Baggage handling is low or medium **AND** Checkin service is no\_answer or low **THEN** Passenger is neutral or dissatisfied \\ \hline \end{tabular}
\end{table} 
Table 5: (Continuation of Table 4) Fuzzy rule bases for SPEA3-based solutions (FRBCs) Nos. 6 and 7 from Figure 3 and Table 3.  
Figure 4: Final shapes of membership functions of input attributes occurring in fuzzy rule bases of Tables 4 and 5. Tables 4 and 5 also reveal an interesting regularity, i.e., the fuzzy rule base of the solution No. \(i\) contains some rule(s) or extension(s) of some rule(s) from the solution No. \(i-1\) (\(i=2,3,\dots\)). Therefore, if the higher accuracy is required then our approach adds some additional fuzzy rules or extends the already existing rules to provide a more detailed (and thus, more accurate) description of the considered classification problem. Such regularity also confirms an internal integrity of our approach. The considered regularity is illustrated--from a bit different angle--in Tables 6-8 (see, first, Part A of Table 6), in which each black square denotes the presence of a given input attribute in the fuzzy rule base of a given solution (FRBC).