val of_pyobject : Py.Object.t -> tval to_pyobject : t -> Py.Object.tval create : param_grid:Py.Object.t -> unit -> tGrid of parameters with a discrete number of values for each.
Can be used to iterate over parameter value combinations with the Python built-in function iter.
Read more in the :ref:`User Guide <grid_search>`.
Parameters ---------- param_grid : dict of string to sequence, or sequence of such The parameter grid to explore, as a dictionary mapping estimator parameters to sequences of allowed values.
An empty dict signifies default parameters.
A sequence of dicts signifies a sequence of grids to search, and is useful to avoid exploring parameter combinations that make no sense or have no effect. See the examples below.
Examples -------- >>> from sklearn.model_selection import ParameterGrid >>> param_grid = 'a': [1, 2], 'b': [True, False] >>> list(ParameterGrid(param_grid)) == ( ... {'a': 1, 'b': True}, {'a': 1, 'b': False},
... {'a': 2, 'b': True}, {'a': 2, 'b': False}) True
>>> grid = {'kernel': ['linear']}, {'kernel': ['rbf'], 'gamma': [1, 10]} >>> list(ParameterGrid(grid)) == {'kernel': 'linear'},
... {'kernel': 'rbf', 'gamma': 1},
... {'kernel': 'rbf', 'gamma': 10} True >>> ParameterGrid(grid)1 == 'kernel': 'rbf', 'gamma': 1 True
See also -------- :class:`GridSearchCV`: Uses :class:`ParameterGrid` to perform a full parallelized parameter search.
val get_item : ind:int -> t -> Py.Object.tGet the parameters that would be ``ind``th in iteration
Parameters ---------- ind : int The iteration index
Returns ------- params : dict of string to any Equal to list(self)ind
val to_string : t -> stringPrint the object to a human-readable representation.
val show : t -> stringPrint the object to a human-readable representation.
val pp : Format.formatter -> t -> unitPretty-print the object to a formatter.