# The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
## 2 Materials and Methods
### Methods
#### 2.2.1 Extreme Gradient Boosting  
The dynamics of real estate markets are complex and influenced by multiple interacting factors. Rather than being straightforward or directly proportional, real estate markets do not always follow a straight or predictable path. Instead of a simple cause-and-effect relationship, where a given change in one factor (like an increase in interest rates) leads to a proportional change in real estate prices, the relationship might be more complex. Small changes in one variable might significantly affect prices under certain conditions and negligible effects under others. Also, multiple factors can influence real estate prices simultaneously, and their combined effect might differ from the sum of their individual effects. For instance, the combination of low interest rates and high demand might push prices up more significantly than expected by considering each factor separately. Therefore, real estate markets exhibit non-linearity and joint effects, which machine learning algorithms adeptly handle [27; 30; 70]. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Feature Name** & **Data Type** & **Mean** & **St. Dev.** & **Min.** & **25\%** & **50\%** & **75\%** & **Max.** & **Skew.** & **Kurt.** &
\begin{tabular}{c} **Corr. with** \\ **Price** \\ \end{tabular} \\ \hline Price & Numerical & 306,046.33 & 155,053.56 & 37,705 & 188,000 & 270,000 & 383,558 & 810,000 & 0.98 & 0.42 & 1 \\ BankEval & Numerical & 2929.44 & 166.91 & 2483 & 2830 & 2979 & 3040 & 3830 & \(-\)0.43 & 0.56 & 0.10 \\ Bedroom & Numerical & 2.22 & 1.16 & 0 & 1 & 2 & 3 & 10 & 0.64 & 0.63 & 0.43 \\ Bus & Numerical & 7.50 & 3.58 & 0 & 5 & 7 & 10 & 23 & 0.73 & 0.88 & \(-\)0.05 \\ Commerce & Numerical & 508.40 & 366.93 & 17.32 & 249.31 & 408.30 & 697.04 & 3133.37 & 1.73 & 5.23 & \(-\)0.15 \\ Conferr Curtis & Numerical & 2106.18 & 378.03 & 1355 & 1871 & 2082 & 2337 & 3172 & 0.50 & 0.17 & 0.04 \\ CPI & Numerical & 0.70 & 0.70 & \(-\)0.70 & 0.10 & 0.60 & 1.00 & 2.70 & 0.80 & 0.63 & 0.03 \\ Culture & Numerical & 259.19 & 205.30 & 3.65 & 118.86 & 212.21 & 357.09 & 2539.90 & 2.72 & 16.19 & \(-\)0.18 \\ EPC & Ordinal & 5.63 & 1.26 & 1 & 5 & 6 & 6 & 9 & \(-\)0.83 & 1.48 & \(-\)0.30 \\ GDP & Numerical & 1.34 & 5.96 & \(-\)17.80 & 1.00 & 2.73 & 3.00 & 17.00 & \(-\)0.70 & 1.75 & 0.01 \\ Health & Numerical & 474.15 & 294.26 & 7.37 & 277.4 & 429.62 & 626.59 & 3296.81 & 2.27 & 12.28 & \(-\)0.05 \\ Latitude & Numerical & 38.73 & 0.02 & 38.69 & 38.72 & 38.73 & 38.74 & 38.80 & 0.62 & \(-\)0.12 & 0.01 \\ Longitude & Numerical & -9.15 & 0.03 & \(-\)9.23 & \(-\)9.16 & \(-\)9.15 & \(-\)9.13 & \(-\)9.09 & \(-\)0.61 & \(-\)0.05 & \(-\)0.07 \\ Parks & Numerical & 331.29 & 187.06 & 5.64 & 196.78 & 300.28 & 421.82 & 1295.44 & 1.19 & 1.97 & \(-\)0.12 \\ PGA & Numerical & 87.29 & 37.90 & 26 & 60 & 79 & 107 & 631 & 1.45 & 4.79 & 0.72 \\ PropCond & Binary & 0.08 & 0.27 & 0 & 0 & 0 & 0 & 1 & 3.18 & 8.14 & 0.21 \\ Safety & Numerical & 87.09 & 525.79 & 17.32 & 502.10 & 769.54 & 1147.63 & 3776.78 & 1.31 & 2.32 & 0.01 \\ School & Numerical & 87.4 & 51.5 & 0 & 5 & 8 & 12 & 30 & 0.90 & 0.80 & 0.02 \\ Security & Numerical & 513.24 & 259.02 & 13.16 & 320.93 & 484.83 & 664.92 & 2073.19 & 0.82 & 1.43 & \(-\)0.10 \\ Sports & Numerical & 148.41 & 81.91 & 7.36 & 86.37 & 135.91 & 194.09 & 560.71 & 0.85 & 0.72 & 0.09 \\ Subway & Numerical & 925.67 & 1123.06 & 3.58 & 319.50 & 520.41 & 988.07 & 634.07 & 2.53 & 6.04 & \(-\)0.10 \\ Train & Numerical & 1096.24 & 713.11 & 18.40 & 638.14 & 983.88 & 1357.03 & 5483.74 & 2.23 & 7.54 & 0.00 \\ Trees & Numerical & 16.73 & 19.43 & 0 & 1 & 10 & 27 & 186 & 1.72 & 4.34 & 0.16 \\ University & Numerical & 699.23 & 387.44 & 9.61 & 414.60 & 641.27 & 914.73 & 2921.03 & 1.23 & 3.01 & \(-\)0.13 \\ UnempRate & Numerical & 6.88 & 0.51 & 5.70 & 6.50 & 6.80 & 7.10 & 8.30 & 0.69 & 0.43 & \(-\)0.06 \\ ZIP & Numerical & 1378.18 & 298.64 & 1000.00 & 1150.31 & 1300.00 & 1600.66 & 1990.62 & 0.64 & \(-\)0.94 & \(-\)0.18 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary statistics for the target variable and features (N = 22,470).