*5.2.1. Single model*

The full dataset is used for this analysis. There is a total number of 17 features, which are Xminutes, Yminutes, %red, %orange, relative humidity, precipitation, pressure, solar radiation, temperature, wind Speed, Xwind, Ywind, CO, NO<sup>2</sup> , O3 , SO2 , PM2.5 (= feature to predict).

The linear regression model obtained after running the algorithm is as follows:


The prediction accuracy of the model is evaluated as

$$\mathbf{r} \qquad \qquad = \mathbf{0.81}$$
