Package | Description |
---|---|
org.dllearner.algorithms.celoe | |
org.dllearner.algorithms.el |
Learning algorithms for the EL description logic.
|
org.dllearner.algorithms.isle | |
org.dllearner.algorithms.isle.metrics | |
org.dllearner.algorithms.ocel |
New experimental refinement operator approach, which takes
obtained information about concrete examples in an algorithm run
stronger into account.
|
org.dllearner.algorithms.qtl.heuristics | |
org.dllearner.core |
Core structure of DL-Learner including the definition of component types and a component manager.
|
org.dllearner.utilities |
Utility classes.
|
org.dllearner.utilities.datastructures |
Utility classesfor manipulating general data structures.
|
Modifier and Type | Class and Description |
---|---|
class |
OEHeuristicRuntime
Search algorithm heuristic for the ontology engineering algorithm.
|
Modifier and Type | Interface and Description |
---|---|
interface |
ELHeuristic
Marker interface for heuristics in the EL learning
algorithms.
|
Modifier and Type | Class and Description |
---|---|
class |
DisjunctiveHeuristic |
class |
StableHeuristic
A stable comparator for search tree nodes.
|
Modifier and Type | Class and Description |
---|---|
class |
NLPHeuristic
TODO: NLP-Heuristiken in Statistik integrieren
|
Modifier and Type | Class and Description |
---|---|
class |
RelevanceWeightedStableHeuristic
A stable comparator for search tree nodes.
|
Modifier and Type | Interface and Description |
---|---|
interface |
ExampleBasedHeuristic
Marker interface for heuristics in the refinement operator
based learning approach.
|
Modifier and Type | Class and Description |
---|---|
class |
FlexibleHeuristic
This heuristic compares two nodes by computing a score
using the number of covered negatives and the horizontal
expansion factor of a node as input.
|
class |
LexicographicHeuristic |
class |
MultiHeuristic
This heuristic combines the following criteria to assign a
double score value to a node:
quality/accuracy of a concept (based on the full training set, not
the negative example coverage as the flexible heuristic)
horizontal expansion
accuracy gain: The heuristic takes into account the accuracy
difference between a node and its parent.
|
class |
NodeComparatorStable
This comparator is stable, because it only takes covered examples, concept
length and the concepts itself (using again a stable comparator) into
account, which do not change during the run of the algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
QueryTreeHeuristic |
class |
QueryTreeHeuristicComplex |
class |
QueryTreeHeuristicSimple
A simple heuristic based which just takes the accuracy into account.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractHeuristic
Search algorithm heuristic for the ontology engineering algorithm.
|
Modifier and Type | Method and Description |
---|---|
static <T extends AbstractSearchTreeNode> |
TreeUtils.toTreeString(T node,
Heuristic<T> heuristic) |
Modifier and Type | Method and Description |
---|---|
Heuristic<T> |
AbstractSearchTree.getHeuristic() |
Constructor and Description |
---|
AbstractSearchTree(Heuristic<T> heuristic)
create a new search tree
|
SearchTree(Heuristic<T> heuristic) |
SearchTreeNonWeak(Heuristic<T> heuristic) |
SearchTreeNonWeakPartialSet(Heuristic<T> heuristic) |
SynchronizedSearchTree(Heuristic<T> comparator) |
DL-Learner is licenced under the terms of the GNU General Public License.
Copyright © 2007-2019 Jens Lehmann