## 4 Analysis and Results  
This section presents the analysis and findings derived from the _IMD Smart City Index Report 2023_[103]. The dataset, which encompassed 140 cities and 45 features, was meticulously prepared through data cleaning to eliminate missing values. A detailed overview of these features is provided in Table 1.  
As noted, data were split randomly into 70% for the training set and 30% for the testing set. The model was tested using 100 trees, and an accuracy of above 90% was achieved. The accuracy test for each number of trees that was tested in the model is shown in Figure 3.  
The maximum accuracy achieved is above 90% when the number of trees is 5, 10, 15, 18, 19, 26, 52, 53, 68, and 100. While these values could have been employed, 100 trees were used in the model. The confusion matrix is presented in Table 2; the evaluation criteria are presented in Table 3. \begin{table}
\begin{tabular}{l l} \hline \hline
**Feature** & **Code** \\ \hline Population & X1 \\ HDI in 2022 & X2 \\ Life expectancy at birth in 2021 & X3 \\ Expected years of schooling in 2021 & X4 \\ Mean years of schooling in 2021 & X5 \\ GNI per capita (\$) in 2021 & X6 \\ Basic sanitation meets the needs of the poorest areas & X7 \\ Recycling services are satisfactory & X8 \\ Public safety is not a problem & X9 \\ Air pollution is not a problem & X10 \\ Medical services provision is satisfactory & X11 \\ Funding housing with rent equal to 30\% or less of a monthly salary is not a problem & X12 \\ Traffic congestion is not a problem & X13 \\ Public transport is satisfactory & X14 \\ Green spaces are satisfactory & X15 \\ Cultural activities (shows, bars, and museums) are satisfactory & X16 \\ Employment-finding services are readily available & X17 \\ Most children have access to a good school & X18 \\ Lifelong learning opportunities are provided by local institutions & X19 \\ Businesses are creating new jobs & X20 \\ Minorities feel welcome & X21 \\ Information on local government decisions is easily accessible & X22 \\ Corruption of city officials is not an issue of concern & X23 \\ Residents contribute to the decision-making of local government & X24 \\ Residents provide feedback on local government projects & X25 \\ Online reporting of city maintenance problems provides a speedy solution & X26 \\ A website or app allows residents to easily give away unwanted items & X27 \\ Free public WiFi has improved access to city services & X28 \\ CCTV cameras have made residents feel safer & X29 \\ A website or app allows residents to effectively monitor air pollution & X30 \\ Arranging medical appointments online has improved access & X31 \\ Car-sharing apps have reduced congestion & X32 \\ Apps that direct you to an available parking space have reduced journey time & X33 \\ Bicycle hiring has reduced congestion & X34 \\ Online scheduling and ticket sales have made public transport easier to use & X35 \\ The city provides information on traffic congestion through mobile phones & X36 \\ Online purchasing of tickets to shows and museums has made it easier to attend & X37 \\ Online access to job listings has made it easier to find work & X38 \\ IT skills are taught well in school & X39 \\ Online services provided by the city have made it easier to start a new business & X40 \\ The current internet speed an reliability meet connectivity needs & X41 \\ Online public access to city finances has reduced corruption & X42 \\ Online voting has increased participation & X43 \\ An online platform where residents can propose ideas has improved city life & X44 \\ Processing identification documents online has reduced waiting times & X45 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of features and corresponding codes. Figure 4 illustrates the mean decrease in accuracy and Gini, depicting each feature's relative importance in the predicted model and the most important factors that can contribute to a smart city ranking. Features with a mean decrease Gini value of more than 1 were grouped.