|
Accord.MachineLearning.DecisionTrees Namespace |
Contains discrete and continuous Decision Trees, with
support for automatic code generation, tree pruning and
the creation of decision rule sets.
Classes| Class | Description | |
|---|---|---|
 | ComparisonExtensions |
Extension methods for ComparisonKind enumeration values.
|
| DecisionBranchNodeCollection |
Collection of decision nodes. A decision branch specifies the index of
an attribute whose current value should be compared against its children
nodes. The type of the comparison is specified in each child node.
|
| DecisionNode |
Decision Tree (DT) Node.
|
 | DecisionTree |
Decision tree (for both discrete and continuous classification problems).
|
| DecisionTreeTraversal |
Common traversal methods for n-ary trees.
|
| DecisionVariable |
Decision attribute.
|
| DecisionVariableCollection |
Collection of decision attributes.
|
| RandomForest |
Random Forest.
|
| RandomForestLearning |
Random Forest learning algorithm.
|
Delegates| Delegate | Description | |
|---|---|---|
 | DecisionTreeTraversalMethod |
Tree enumeration method delegate.
|
Enumerations| Enumeration | Description | |
|---|---|---|
 | ComparisonKind |
Numeric comparison category.
|
| DecisionVariableKind |
Attribute category.
|
See AlsoReference
Accord.MachineLearning.DecisionTrees