# Multi-Objective Unsupervised Feature Selection and Cluster Based on Symbiotic Organism Search
## 4 Experimental Settings
### Investigating the Impact of Different SOS Parameters on Cluster SOS  
The aim of this section is to examine how the algorithms' solutions have evolved over generations under various configurations for a single parameter. This is ecoNeco_size, where ecoNeco_size is the quantity of documents and the number of groups, both of which are user-specified. Given these conditions, this section focuses on highlighting the effect of a single parameter changes. Specifically, the following three scenarios have been tested and are displayed in Table 4. Empirical research has also demonstrated that the best results can be obtained with a linear relationship between ecoNeco_size and the number of clusters. All scenarios were tested over ten runs, with a maximum number of iterations fixed at 100 for all runs. The fitness function value is the ADDC value of the solution. The SOS algorithm, which is covered in Section 5, is the evaluation algorithm. \(d_{max}\) = 1 \(\times\) 10\({}^{3}\) was obtained using the Routers dataset. The evolution of the solution for various SOS parameter values as clusters shows that when ecoNeco_size is decreased, the solution is found more slowly than when ecoNeco_size is increased, which causes the solution to be found faster than when ecoNeco_size is small. Nevertheless, with the benefits of reducing the required amount of space and converging to the optimal result, using the appropriate ecoNeco_size seems to be a reasonable and logical choice. In addition, doubling the number of clusters (8 \(\times\) 2 in this dataset) can yield the best results with a specific selection of ecoNeco_size. \begin{table}
\begin{tabular}{c c} \hline \hline
**Scenarios** & \(\boldsymbol{eco_{Neco\_size}}\) \\ \hline
1 & 8 \\
2 & 16 \\
3 & 24 \\
4 & 32 \\
5 & 40 \\
6 & 48 \\
7 & 56 \\
8 & 64 \\
9 & 72 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Some scenarios of the parameters’ symbiotic organisms search as the feature selection. Performance Measurement and Datasets  
The universal F-measure from [63] was used in this study to evaluate the external condition. The F-measure, which takes into account recall and accuracy of information retrieval, is high if clusters are ideal. Each class is expected to have its own set of essential documents, and each class will continue to have its required document compilation. Higher F-measure values indicate better clustering performance, with a metric comprising a range of 0 to 1. Equation (21) shows the mathematical expression of F-measures for cluster \(j\) and class \(i\):  
\[\mathrm{F}(i,j)=\frac{2\mathrm{Recall}(i,j)\times\mathrm{Precision}(i,j)}{ \mathrm{Recall}(i,j)+\mathrm{Precision}(i,j)}. \tag{21}\]  
Equation (22) is used to determine the overall value for the F-measure, which is taken as in the weighted average of all. \[\mathrm{F}=\sum_{i}\frac{n_{i}}{N}maxF(i,j) \tag{22}\]  
Thus, the F-measure values are distributed across the interval (0,1), and the values are proportional to higher levels of clustering quality. This study used four independent and separate datasets to conduct a thorough evaluation of algorithm performance. This approach guaranteed an exhaustive and objective evaluation and comparison of the algorithms. The main dataset, known as classic 3, was used as a benchmark for comparison during the text-mining process. There are 3892 documents in the collection, which have been classified into three groups. In particular, there are 1460 documents centered on information retrieval (CISI), 1033 documents referring to medical problems (MEDs), and 1399 documents related to aviation systems (CRANs) [64]. The second dataset was made up of 1445 CNN news articles that were selected from the TDT2 and TDT3 corpora. Replicating the dataset, the i-Event experiment uses information from the TDT2 and TDT3 corpora [65]. A significant number of chosen documents are usually required to experiment and create clusters on the user interface. The concision of CNN's reporting and the significance of the events they covered also had a role in the choice of these sources.