IGWOInto the Great Wide Open (Tom Petty song)
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The IGWO is mainly used to adaptively search the feature space for best feature combination.
The pseudocode of the IGWO algorithm is presented as shown in pseudocode 2.
The IGWO, GWO, and GA were implemented from scratch.
To observe the optimization procedure of the algorithms including GA, GWO, and IGWO, the iteration process was recorded in Figure 8.
Figure 11 shows the optimization procedure of the algorithms including GA, GWO, and IGWO. It can be observed from Figure 11 that the fitness curve of IGWO completely converges after the 24th iteration, while the fitness curve of GWO and GA just started to converge from the 28th iteration and the 43rd iteration, respectively.
In the first step, PSO is firstly used to generate the initial positions of population, and then IGWO is used to select best feature combination by searching for the feature space adaptively.
In order to further improve the performance of the SVM model, we evaluated the proposed IGWO strategy enhanced SVM approach on the same data.
Hence, the SVM constructed based upon IGWO can lead to a more stable classification result for selecting a second major than the others.
It can be seen that the SVM model trained via IGWO exhibits an obvious advantage over the other SVM methods in terms of not only convergence rate, but also the quality of solution, and it takes only 22 iterations to achieve the best fitness.
On the other hand, it also suggests that the IGWO strategy can pick out the most discriminative features from the dataset compared to the other three comparative counterparts.