rithm on specific dataset howeverit is often used in conjunction with parameter search methods like grid search for this reasonmany people use the term cross-validation colloquially to refer to grid search with cross-validation the overall process of splitting the datarunning the grid searchand evaluating the final parameters is illustrated in figure - in[ ]mglearn plots plot_grid_search_overview(figure - overview of the process of parameter selection and model evaluation with gridsearchcv because grid search with cross-validation is such commonly used method to adjust parametersscikit-learn provides the gridsearchcv classwhich implements it in the form of an estimator to use the gridsearchcv classyou first need to specify the parameters you want to search over using dictionary gridsearchcv will then perform all the necessary model fits the keys of the dictionary are the names of parameters we want to adjust (as given when constructing the model--in this casec and gamma)and the values are the parameter settings we want to try out trying the values and for and gamma translates to the following dictionaryin[ ]param_grid {' '[ ]'gamma'[ ]print("parameter grid:\ {}format(param_grid)out[ ]parameter grid{' '[ ]'gamma'[ ]grid search