[−][src]Crate spaces
Set/space primitives for defining machine learning problems.
spaces
provides set/space primitives to be used for defining properties of
machine learning problems. Traits such as Space
, and it's derivatives, may
be used to define state/action spaces, for example. Mappings between
different spaces may also be defined using traits such as Surjection
to
streamline many common preprocessing and type conversion tasks.
Modules
discrete | Discrete spaces module. |
real | Real spaces module. |
Structs
Empty | A space filled with... nothing. |
Equipartition | Finite, uniformly partitioned interval. |
Interval | Generalisation of a interval. |
PairSpace | 2-dimensional heterogeneous space. |
ProductSpace | N-dimensional homogeneous space. |
TwoSpace | 2-dimensional homogeneous space. |
Enums
Card | Measure of the cardinality (#) of a set. |
Dim | Measure of the dimensionality of the elements of a set. |
Traits
BoundedSpace | Trait for defining spaces with at least one finite bound. |
FiniteSpace | Trait for defining spaces containing a finite set of values. |
Intersection | Trait for types that can be combined in the form of an intersection. |
Space | Trait for defining geometric spaces. |
Surjection | Trait for types that implement a mapping from values of one set onto another. |
Union | Trait for types that can be combined in the form of a union. |