# Fire Risk Assessment Models Using Statistical Machine Learning and Optimized Risk Indexing
## 4 Experimental Results
Average of damaged area, Spread of fire, Inspection year, Inspection period, Property number, Name of property, Address1, Address2, Address3, Address4, Address5, Address6, Fiscal year of the report, Inspection date, Sort1, Sort2, Sort3, Estimated property value, Estimated value of machine, Estimated total value, Important level, KFRI 1, KFRI(before discount rate), Maximum Possible Loss, Estimated Maximum Loss, Year of construction 1, Building structure class, Number of buildings, Number of floor, Number of underground floor, Total area of buildings, Number of total floor, Building structure, Building size, Multiple use 1, Multiple use 2, Movement of occupants 1, Movement of occupants 2, Accommodation 1, Accommodation 2, Fire load, Fire facility, Gas facility, Hazardous material facility, Electricity facility, Basic process 1, Basic process 2, Hazardous material, Hot work, Flammable gas, High temperature or pressure, Static electricity, Dust, High voltage, Safety management 1, Safety management 2, Fire extinguisher 1, Protected ratio by Fire extinguisher, Fire extinguisher 2, Standpipe 1, Protected ratio by standpipe, Standpipe 2, Hydrant 1, Protected ratio by hydrant, Hydrant 2, Sprinkler 1, Protected ratio by sprinkler, Sprinkler 2, Total flooding gas system 1, Protected ratio by total flooding gas system, Total flooding gas system 2, Fire detection system 1, Protected ratio by fire detection system, Fire detection system 2, Emergency alarm system 1, Protected ratio by emergency alarm system, Emergency alarm system 2, Emergency notifying system 1, Emergency notifying system 2, Fire compartment 1, Fire compartment 2, Evacuation system 1, Evacuation system 2, Smoke control system 1, Smoke control system 2, Smoke control system 3, Auxiliary equipment required for fire brigade 1, Auxiliary equipment required for fire Public Fire Service 3, Public Fire Service 4, Additional insurance discount, Distance between buildings, Type of report, Year of construction 2, Year of construction 2, KFRI 2, KFRI 3, Percent rank of KFRI, KFRI 4, Percent rank of KFRI 4, Likelihood of KFRI 1, Percent rank of likelihood of KFRI 1, Likelihood of KFRI 4, Percent rank of likelihood of KFRI 4, Likelihood of KFRI 5, Percent rank of likelihood of KFRI 5, Likelihood of KFRI 6, and Percent rank of likelihood of KFRI 6. We applied fire risk index of each building and factory for our proposed methods. First, we carried out logistic regression for fire risk forecasting. The response variable (\(\Upsilon\)) is the occurrence result of fire (1: occurred fire, 0: not occurred fire) and the explanatory variables are 106 variables except Y. To select the significant variables (features) explaining Y significantly, we used p-value (probability value) of each variable in the following hypothesis [10]:  
\[H_{0}:\beta_{i}=0\ \ \ vs.\ \ H_{1}:\beta_{i}\
eq 0 \tag{5}\]  
where  
\(\beta_{i}\): model parameter of _ith_ variable \(X_{i}\)  
We reject the null hypothesis \(H_{0}\) when p-value is less than 0.05 (95% confidence level). This means that \(X_{i}\) explains Y significantly. Using this feature selection process, we selected 18 variables from an entire 106 variables as follows: Year of construction (\(<2\times 10^{-16}\)), Number of total floor (\(<2\times 10^{-16}\)), Building structure (\(<2\times 10^{-16}\)), Building size (\(<2\times 10^{\times}\)), Fire load (\(1.70\times 10^{-12}\)), Fire facility (\(3.08\times 10^{-5}\)), Gas facility (\(8.71\times 10^{-10}\)), Hazardous material facility (\(<2\times 10^{-16}\)), Electricity facility (\(4.39\times 10^{-12}\)), Basic process (\(<2\times 10^{-16}\)), Hazardous material (\(<2\times 10^{-16}\)), Hot work (0.00089), Flammable gas (0.0138), High temperature or pressure (\(1.86\times 10^{-7}\)), Static electricity (0.000418), Dust (\(<2\times 10^{-16}\)), High voltage (\(1.15\times 10^{-12}\)), and Safety management (0.0429). The value in parenthesis for each variable is the p-value.