Table 5: Confusion matrix GLM model fit on Kariki_Farm data with interaction detection using RST
From the experiment, we see that the GLM model, modeled using the detected interaction terms from the Rough Set theory method, performed better in accuracy compared to the model without the detected interactions. Seeing these interactions helped determine the essential features necessary for predicting the weather, reduced the dimensionality of the data, and ultimately improved the accuracy of the GLM model. The table below shows these results: