This extension intends to solve #1020 for regular grids: it provides an index into the grid points output by ParameterGrid, such that results from GridSearchCV (particularly when returned as an array as in #1787) can be accessed by parameter value.

For example, I could get the mean test_score for each 'max_depth' value:

grid_search = GridSearchCV(clf, {'max_depth': range(1, 5), 'max_features': range(1, 3)})
grid_search.fit(...)
grid = ParameterGrid(grid_search.param_grid) # should we make it easier to get the ParameterGrid?
keys, index = grid.build_index(['max_depth'], ravel=True)
indexed = np.array(candidate.mean_validation_score for candidate in [grid_search.cv_scores_])[index]
print(indexed.mean(axis=1))

This PR aims to account for most of the functionality of #1034 within the current parameter search framework. The examples from there should be adopted.