\label{FFSOLSLogPriceSubsubsection}
The 10 models resulting from the cross-validation are presented in Figure \ref{FsRegressionVariablesLog}. One can see that now 89 % of the price is explained by the attributes, which is slightly more than for the models based on the original data (0.87). Therefore, this is a first argument in favor of the log model.
Once again, one can note certain variables are more stable than other, especially ’Curbweight’, ’Horsepower’, ’Eur’ (which was not significant in the models on the original data) and ’Brand123’. On the other hand, variables such as ’CompressionRatio’, ’DriveWheelFwd’, ’DriveWheelRwd’ and ’Fuel’ only appear in one of the 10 best models.