## 5 Results and Discussions  
### Distribution of Datasets  
The most important step is to determine the underlying distribution of data before applying any ML approach. In an ML context, the input data for processing comprise only numerical values. A histogram is a visual representation of the dataset distribution that shows any outliers or gaps in the data. ML performance depends on the distribution of the datasets. If the data distribution is not normal, then it can be skewed to the left or right or be completely random. Whether or not the shear wave velocity obtained from the field is normally distributed is discussed below. After analyzing Figure 12a-l, it can be concluded that all of the datasets after 3 m are positively skewed. Moreover, the layers are contaminated with the outliers found after 3 m of depth. Another observation from Table 2 is that the number of observations decreases with the increase of depth. However, a wide range of data points with the increase of depth can be observed in the histogram. Figure 12a illustrates the histogram of V\({}_{\text{S}}\) of 0-0.5 m depth. The histogram has a maximum value of 116.79 ms\({}^{-1}\) and a minimum value of 0 ms\({}^{-1}\). The frequency is zero within 81.36-90.21 ms\({}^{-1}\) and 214.22-240.79 ms\({}^{-1}\). Figure 12b illustrates the histogram of V\({}_{\text{S}}\) at 0.5-1 m depth, and the majority of the values of shear wave velocity lie in the range of 120.47-250.67 ms\({}^{-1}\). The frequency is zero between 258.81 and 275.09 ms\({}^{-1}\). The maximum value of the third histogram (Figure 12c) is 173.71 ms\({}^{-1}\), with the lowest being 0 ms\({}^{-1}\). Two outliers at 12.06 and 402.7 ms\({}^{-1}\) can be observed in the datasets. Besides, five nonfrequency ranges, from 12.06-92.89, 106.35-133.29, 200.65-214.12, 254.53-267.99, and 294.93-389.23 ms\({}^{-1}\), can be found in the datasets. Figure 12d is the histogram of V\({}_{\text{S}}\) at 1.5-2 m depth. This data can be defined as being normally distributed. The majority of the values of shear wave velocity lie in the range of 155.66-285.45 ms\({}^{-1}\). No outliers can be observed in the dataset. The histogram of the V\({}_{\text{S}}\) at 2-2.5 m depth is depicted in Figure 12e. It has one peak at 219.93 ms\({}^{-1}\) and two gaps (zero frequency) within 86.47-136.52 and 336.7-353.38 ms\({}^{-1}\). The histogram at 2-2.5 m depth follows a similar pattern to the fourth histogram. Figure 12f shows the histogram of the V\({}_{\text{S}}\) at 2.5-3 m depth. There is one outlier at 459.79 ms\({}^{-1}\) of V\({}_{\text{S}}\). Figure 12: _Cont._ \begin{table}
\begin{tabular}{c c c} \hline
**Algorithm** & **Parameter** & **Setting** \\ \hline SVR & C & 1 \\  & Kernel & RBF \\  & Epsilon & 0.2 \\  & Maximum iteration & \(-1\) \\ LR & Fit intercept & True \\  & n jobs & None \\ \hline \end{tabular}
\end{table} 
Table 3: _Cont._Figure 12: Cont. The histogram of the \(\rm V_{S}\) at 3-3.5 m depth is emphasized in Figure 12g. These datasets are right or positively skewed. They also contain a significant number of outliers. The majority of the data can be found in the 206.65-251.24 \(\rm ms^{-1}\) range, and the outliers are found from 429.6 to 697.14 \(\rm ms^{-1}\). The histogram of \(\rm V_{S}\) at 3.5-4 m depth shows a similar pattern to the histogram at 3-3.5 m. The distribution of the datasets is also right skewed, as shown in Figure 12h. These datasets are contaminated with outliers detected from 322.59-697.14 \(\rm ms^{-1}\). Figure 12j also depicts that the histogram of \(\rm V_{S}\) at 4-4.5 m and that of 4.5-5 m layers of depth are right skewed. Moreover, the outliers were detected from 421.46-799.44 \(\rm ms^{-1}\) at 4-4.5 m and 455.36-875.71 at 4.5-5 m depth. Figure 12k,l illustrates that the \(\rm V_{S}\) histograms at 5-5.5 and 5.5-6 m layers of depth are right or positively skewed. Both layers are highly contaminated with the outliers detected from 857.49-1541.83 \(\rm ms^{-1}\) at 5-5.5 m depth and 512.79-1361.85 \(\rm ms^{-1}\) at 5.5-6 m depth.