This class encapsulates the C4.5 Algorithm used to generate a decision tree (see Grail.Simulation.DecisionTree) based on the dataset provided.
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DecisionNode< TDecisionType > | ConstructTree (Dataset< TDecisionType > dataset, int maxDepth=int.MaxValue) |
| Constructs a new decision tree based on the provided dataset. The decision type is given by generic argument TDecisionType. More...
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HashSet< int > | UsedColumns = new HashSet<int>() [get] |
| Gets indices of columns in the dataset used for learning with the C4.5 Algorithm that were actually used when creating the decision tree. More...
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This class encapsulates the C4.5 Algorithm used to generate a decision tree (see Grail.Simulation.DecisionTree) based on the dataset provided.
- Template Parameters
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◆ ConstructTree()
Constructs a new decision tree based on the provided dataset. The decision type is given by generic argument TDecisionType.
- Parameters
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dataset | A dataset that contains training data for the decision tree |
maxDepth | Optionally, you may limit the depth of the decision tree to @maxDepth most important levels |
- Returns
◆ UsedColumns
Gets indices of columns in the dataset used for learning with the C4.5 Algorithm that were actually used when creating the decision tree.
The documentation for this class was generated from the following file:
- GrailSimulatedGames/source/SimulatedGames/OfflineLearning/C45Algorithm.cs