Package | Description |
---|---|
org.dllearner.algorithms.qtl |
Learning algorithm based on so-called query trees
which are a tree based representation of a (set of) RDF resource(s)
|
org.dllearner.algorithms.qtl.datastructures.impl | |
org.dllearner.algorithms.qtl.heuristics |
Modifier and Type | Method and Description |
---|---|
EvaluatedRDFResourceTree |
QTL2DisjunctiveMultiThreaded.getBestSolution() |
EvaluatedRDFResourceTree |
QTL2Disjunctive.getBestSolution() |
Modifier and Type | Method and Description |
---|---|
SortedSet<EvaluatedRDFResourceTree> |
QTL2DisjunctiveMultiThreaded.getSolutions() |
SortedSet<EvaluatedRDFResourceTree> |
QTL2Disjunctive.getSolutions() |
List<EvaluatedRDFResourceTree> |
QTL2DisjunctiveMultiThreaded.getSolutionsAsList() |
List<EvaluatedRDFResourceTree> |
QTL2Disjunctive.getSolutionsAsList() |
Modifier and Type | Method and Description |
---|---|
int |
EvaluatedRDFResourceTree.compareTo(EvaluatedRDFResourceTree other) |
Modifier and Type | Method and Description |
---|---|
int |
QueryTreeHeuristic.compare(EvaluatedRDFResourceTree tree1,
EvaluatedRDFResourceTree tree2) |
double |
QueryTreeHeuristic.getMaximumAchievableScore(EvaluatedRDFResourceTree tree)
Returns the maximum achievable score according to the used score
function.
|
double |
QueryTreeHeuristic.getNodeScore(EvaluatedRDFResourceTree node) |
double |
QueryTreeHeuristicComplex.getScore(EvaluatedRDFResourceTree tree) |
abstract double |
QueryTreeHeuristic.getScore(EvaluatedRDFResourceTree tree) |
double |
QueryTreeHeuristicSimple.getScore(EvaluatedRDFResourceTree tree) |
DL-Learner is licenced under the terms of the GNU General Public License.
Copyright © 2007-2019 Jens Lehmann