## 5 Results Summary and Conclusions
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Criterion**} & \multicolumn{3}{c}{**8 Clusters**} & \multicolumn{3}{c}{**10 Clusters**} \\  & **Stage 1** & **Stage 2** & **Stage 3** & **Stage 1** & **Stage 2** & **Stage 3** \\ \hline No. of audiograms & 55 & 48 & 47 & 55 & 51 & 49 \\ Silhouette Criterion Values 1 & 0.3907 & 0.4640 & 0.4814 & 0.3814 & 0.4239 & 0.4461 \\ Calinski-Harabasz Criterion & & & & & & \\ Values 1 & 36.7956 & 38.5503 & 38.5476 & 34.6120 & 37.3905 & 37.3974 \\ Davies-Bouldin Criterion Values 2 & 1.0427 & 0.9670 & 0.9426 & 1.0424 & 1.0329 & 1.0234 \\ No. of classified audiograms & & & & & & \\ Population & & & & & & \\ Silhouette Criterion Values for & & & & & & \\ audiograms population & & & & & & \\ Calinski-Harabasz Criterion & & & & & & \\ Values for audiograms population & & & & & & \\ Davies-Bouldin Criterion Values & & & & & & \\  & 0 & 0 & 0 & 0 & 0 & \\  & 0.0502 & 0.0364 & 0.0357 & 0.0503 & 0.0284 & 0.0305 \\  & 0.1313 & 0.0842 & 0.0795 & 0.1312 & 0.1010 & 0.0991 \\  & 0.2077 & 0.1636 & 0.1548 & 0.2078 & 0.1735 & 0.1403 \\ Eigenvalues & 0.2749 & 0.2667 & 0.2727 & 0.2750 & 0.2665 & 0.2790 \\  & 0.3700 & 0.2978 & 0.3163 & 0.3693 & 0.3155 & 0.3239 \\  & 0.4163 & 0.3735 & 0.3914 & 0.4153 & 0.3589 & 0.3620 \\  & 0.5062 & 0.4122 & 0.4137 & 0.5060 & 0.4045 & 0.4607 \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\ \hline \hline \end{tabular} \({}^{1}\) Max for an optimal number of clusters. 2 Min for an optimal number of clusters.  
\end{table} 
Table 7: Summary of different clustering evaluation criteria. current practice, trials are made to mask the hearing frequency band with a large number of filters with complex techniques. Another consequence to these complex designs the process of adjusting hearing aid becomes difficult for both the patients and audiologists. Instead of attempting to match different types of hearing loss with one design to satisfy the needs of many patients aiming to lower the cost of manufacturing, designs can be implemented according to categories produced by our intelligent solution. The filter bank can be designed to match the shapes of a number of these clusters not all. This will result in designs that less complex, with low delay, a small chip area, and reduced cost. In addition, these clusters will facilitate the process of programming or adjusting hearing aid to match the user needs by assigning each patient's audiogram a configuration related to the produced clusters. Consequently, configuring a hearing aid will be easy and less exhausting for the patients and the audiologists as it will require less response from the patients. The power of intelligent solutions does not depend on the skills, experience, and knowledge of limited number of skillful experienced audiologists. In addition, as it requires less response from the patients, it will introduce big help to cohorts such as older people, individuals with dementia and children who are experience hearing loss. In addition, this method can be applied to any set of test frequencies as it is not restricted to the used set in the study. Data can be pre-processed such that any missed frequency can be interpolated. The needed input is the hearing levels to be tested at eight different frequencies. Those eight frequencies can vary according to the protocol used in the hearing test. Hence, what is considered in this study is to test the air conduction thresholds at eight test frequencies with/without masking in the non-test ear. Bone conduction thresholds are not considered in this study. To conclude, the authors do not count only on rigid statistical analysis. The results should be interpreted according to the needed solution to be introduced. The authors prefer to consider the 10 clusters since more shapes of patients' audiograms will be included. In addition, the authors predict that grouping the standard levels S1, N1, N2, and N4, N5 in the same cluster might be a source of confusion for any future supervised machine learning algorithm.