## 5 Results and Discussion
It shows the number of samples that fall in each class i.e., poor, bad, medium and excellent. It can be seen that with NSFWQI, more than 75% of the data remains unclassified, even with weight updates. This, in turn, proves that the results achieved with the EWQI are reliable and accurate. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Feature Weighting Method** & **No. of Parameters** & **Score** & **Accuracy** \\ \hline \multirow{8}{*}{XGB} & \multirow{8}{*}{20} & chl-\(\alpha\): 0.00183 & \(NO_{2}\): 0.03497 & \multirow{8}{*}{98.46\%} \\  & & DO: 0.07315 & \(O_{2}\): 0.02866 & \\  & & EC: 0.19124 & \(SO_{2}\): 0.00398 & \\  & & pH: 0.04043 & \(SO_{2}\): 0.00398 & \\  & & SDD: 0.12290 & HCHO: 0.01529 & \\  & & TDS: 0.08795 & \(CH_{4}\): 0.00246 & \\  & & Tur: 0.00593 & Aspect: 0.00316 & \\  & & Air Temperature: 0.00382 & Slope: 0.00147 & \\  & & Precipitation: 0.02134 & Lithology: 0.33722 & \\  & & Wind: 0.01571 & Landcover: 0.00314 & \\  & & CO: 0.00534 & & \\ \hline \multirow{8}{*}{RF} & \multirow{8}{*}{22} & chl-\(\alpha\): 0.04159 & \(NO_{2}\): 0.02785 & \multirow{8}{*}{98.46\%} \\  & & DO: 0.08917 & \(O_{3}\): 0.03457 & \\  & & EC: 0.13447 & \(SO_{2}\): 0.00452 & \\  & & pH: 0.09033 & HCHO: 0.01582 & \\  & & SDD: 0.06160 & \(CH_{4}\): 0.00056 & \\  & & TDS: 0.11201 & Aspect: 0.00520 & \\  & & Tur: 0.04504 & Slope: 0.00955 & \\  & & Air Temperature: 0.00448 & Lithology: 0.14103 & \\  & & Precipitation: 0.00896 & Soil Type: 0.00087 & \\  & & Wind: 0.00844 & Landcover: 0.01397 & \\  & & CO: 0.01142 & Geology: 0.13857 & \\ \hline \multirow{8}{*}{LGBM} & \multirow{8}{*}{21} & chl-\(\alpha\): 269.0000 & \(NO_{2}\): 790.00000 & \multirow{8}{*}{99.11\%} \\  & & DC: 1092.0000 & \(O_{3}\): 1072.0000 & \\  & & EC: 790.0000 & \(SO_{2}\): 287.0000 & \\  & & pH: 1181.00000 & HCHO: 735.00000 & \\  & & SDD: 1287.00000 & \(CH_{4}\): 98.00000 & \\  & & TDS: 777.0000 & Aspect: 390.00000 & \\  & & Tur: 221.0000 & Slope: 489.0000 & \\  & & Air Temperature: 337.00000 & Lithology: 482.00000 & \\  & & S9: 325.00000 & Soil Type: 9.0000 & \\  & & Wind: 325.00000 & Landcover: 368.00000 & \\  & & CO: 676.00000 & & \\ \hline \multirow{8}{*}{CatB} & \multirow{8}{*}{22} & chl-\(\alpha\): 1.96433 & \(NO_{2}\): 3.83250 & \multirow{8}{*}{99.34\%} \\  & & DO: 10.02918 & \(O_{3}\): 5.40983 & \\  & & EC: 12.98044 & \(SO_{2}\): 1.50510 & \\  & & pH: 69.98978 & HCHO: 3.38323 & \\  & & SDD: 6.19110 & \(CH_{4}\): 0.13716 & \\  & & TDS: 5.29395 & Aspect: 1.13175 & \\  & & Tur: 3.04026 & Slope: 1.91270 & \\  & & Air Temperature: 1.40388 & Lithology: 11.99015 & \\  & & Precipitation: 1.21085 & Soil Type: 0.10634 & \\  & & Wind: 1.76956 & Landcover: 1.96139 & \\  & & CO: 2.32570 & Geology: 15.43083 & \\ \hline \multirow{8}{*}{AdaB} & \multirow{8}{*}{16} & DO: 0.08000 & \(NO_{2}\): 0.04000 & \multirow{8}{*}{98.46\%} \\  & & EC: 0.10000 & \(O_{3}\): 0.06000 & \\  & & PH: 0.08000 & \(SO_{2}\): 0.06000 & \\ \cline{1-1}  & & SDD: 0.10000 & HCHO: 0.02000 & \\ \cline{1-1}  & & PDS: 0.12000 & Slope: 0.10000 & \\ \cline{1-1}  & & Precipitation: 0.04000 & Lithology: 0.02000 & \\ \cline{1-1}  & & Wind: 0.02000 & Landcover: 0.04000 & \\ \cline{1-1}  & & CO: 0.04000 & Geology: 0.08000 & \\ \hline \hline \end{tabular}  
* The first highest accuracy achieved \({}^{2}\) The second highest accuracy achieved.  
\end{table} 
Table 4: Feature weighting method results on the training data.