skopt.space.space
.Categorical¶
- class skopt.space.space.Categorical(categories, prior=None, transform=None, name=None)[source][source]¶
Search space dimension that can take on categorical values.
- Parameters
- categorieslist, shape=(n_categories,)
Sequence of possible categories.
- priorlist, shape=(categories,), default=None
Prior probabilities for each category. By default all categories are equally likely.
- transform“onehot”, “string”, “identity”, “label”, default=”onehot”
“identity”, the transformed space is the same as the original space.
“string”, the transformed space is a string encoded representation of the original space.
“label”, the transformed space is a label encoded representation (integer) of the original space.
“onehot”, the transformed space is a one-hot encoded representation of the original space.
- namestr or None
Name associated with dimension, e.g., “colors”.
- Attributes
- bounds
- is_constant
- name
- prior
- size
- transformed_bounds
- transformed_size
Methods
distance
(a, b)Compute distance between category
a
andb
.Inverse transform samples from the warped space back into the original space.
rvs
([n_samples, random_state])Draw random samples.
set_transformer
([transform])Define _rvs and transformer spaces.
transform
(X)Transform samples form the original space to a warped space.
- distance(a, b)[source][source]¶
Compute distance between category
a
andb
.As categories have no order the distance between two points is one if a != b and zero otherwise.
- Parameters
- acategory
First category.
- bcategory
Second category.
- inverse_transform(Xt)[source][source]¶
Inverse transform samples from the warped space back into the original space.
- rvs(n_samples=None, random_state=None)[source][source]¶
Draw random samples.
- Parameters
- n_samplesint or None
The number of samples to be drawn.
- random_stateint, RandomState instance, or None (default)
Set random state to something other than None for reproducible results.