Grail.SimulatedGames.OfflineLearning Namespace Reference

Classes
class	C45Algorithm
	This class encapsulates the C4.5 Algorithm used to generate a decision tree (see Grail.Simulation.DecisionTree) based on the dataset provided. More...
class	C45Counter
class	C45IterationParameters
class	C45SingleIterationResult
class	C45ValueDecisionCounter
class	Dataset
	Container for data in form of [consideration_values][decision], where consideration values are [float, float,...,float] and decision is TDecisionType. USe it for training the decision tree. More...
class	DatasetSample
	Represents elements stored in DataSet. They consist of a vector of consideration values and decision made under those considerations. More...
class	HashSetExtensions
interface	IVectorizer
	Classes implementing this interface provide training data in the offline learning process. More...
class	OfflineLearner
	This is the main class you will use to peform the offline learning process. Assign it to the unit of a SimulatedGame. It will gather properly vectorized data. You get access to this data by methods of this class. More...
class	TreeDataSample
	Structure for storing results in UniqueTreeDataset. More...
class	UniqueTreeDataset
	A class that stores samples, which are values for given considerations (conditions in decision tree) together with statistics of decisions performed under those considerations. When the learning process is stopped, then you can convert this object to a flat Dataset, that picks the most frequently chosen decision for each sample. More...

Enumerations
enum	DecisionConsiderationType { NOMINAL = 0, NUMERIC }
	Defines possible types of considerations (conditions). NOMINAL: represents a switch on values (SWITCH(A): CASE X1...; CASE X2:...; ... CASE XN:...) NUMERIC: represents less than value and greater than value conditions If you need more information, please consult the offline learning manual page. More...

Enumeration Type Documentation

DecisionConsiderationType

enum Grail.SimulatedGames.OfflineLearning.DecisionConsiderationType

strong

Defines possible types of considerations (conditions). NOMINAL: represents a switch on values (SWITCH(A): CASE X1...; CASE X2:...; ... CASE XN:...) NUMERIC: represents less than value and greater than value conditions If you need more information, please consult the offline learning manual page.