## 5 Conclusions  
The article presents the results of the experimental verification of the mathematical model that is based on the random forest algorithm for quantitatively assessing the moisture content in historical brick walls. Such validation is a novelty because similar research has not been conducted to date. It is, however, necessary before implementing the method to construction practice. The verification was carried out on a newly built data set based on archival and experimental research conducted on two newly selected historical buildings of different ages.  
Based on the conducted research and analyzes which aimed to validate the suitability of the model based on the random forest algorithm for the method of the non-destructive quantitative assessment of the humidity content of historical brick walls (developed earlier by the author), the following conclusions can be drawn:  
* It is possible to reliably assess the mass moisture content of a historical brick wall using the model based on the random forest algorithm, and also using parameters assessed using the non-invasive dielectric and microwave methods, the semi-quantitative method, and archival research;
* The correct mapping by the RF model of the actual mass moisture content \(U_{m}\) is evidenced by the low values of the median of absolute error \(\mid\!\Delta U_{m}\!\mid\) amounting to 1.79% for the Golden Gate in Gdansk and 1.46% for the tenement house in Katowice, and the not too high (for in situ tests) median of the relative error \(\mid\!RE\!\mid\) amounting to 16.70% and 13.75% for these buildings, respectively. The height of the error may be the result of the inaccuracy of the data entered into the model. It should be noted that the conditions of conducting in situ tests in historical buildings are often difficult, which is associated with possible inaccuracies in measurements conducted with the use of experimental methods;
* The average values of the humidity content \(U_{mc}\) identified with the use of the RF model are close to the average values of the humidity content \(U_{m}\) gained during the research using the gravimetric method.  
Further validation works are planned for different historical buildings, and they may result in the implementation of the developed model into construction practice. Based on the obtained results, decisions will be made regarding the possible continuation of work in order to better match the algorithm to the data, e.g., by optimizing the model parameters, or by using other machine learning algorithms such as deep neural networks. At present, it seems that the accuracy of the developed model is sufficient for the needs of the construction industry, and the results of the analyzes obtained to date are satisfactory.  
Figure 7: Histograms of the relative error \(\mid\!RE\!\mid\) determined for the RF-generated \(U_{mc}\) values in the case of: (**a**) the Golden Gate building in Gdansk, and (**b**) the tenement house in Katowice.  
Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Data is contained within the article. Conflicts of Interest: The author declares no conflict of interest.