each point in the heat map corresponds to one run of cross-validationwith particular parameter setting the color encodes the cross-validation accuracywith light colors meaning high accuracy and dark colors meaning low accuracy you can see that svc is very sensitive to the setting of the parameters for many of the parameter settingsthe accuracy is around %which is quite badfor other settings the accuracy is around we can take away from this plot several things firstthe parameters we adjusted are very important for obtaining good performance both parameters ( and gammamatter lotas adjusting them can change the accuracy from to additionallythe ranges we picked for the parameters are ranges in which we see significant changes in the outcome it' also important to note that the ranges for the parameters are large enoughthe optimum values for each parameter are not on the edges of the plot now let' look at some plots (shown in figure - where the result is less idealbecause the search ranges were not chosen properlyfigure - heat map visualizations of misspecified search grids grid search