Modifier and Type | Field and Description |
---|---|
private KNNQuery<O,D> |
LOF.LOFResult.kNNReach
The kNN query w.r.t. the reachability distance.
|
private KNNQuery<O,D> |
LOF.LOFResult.kNNRefer
The kNN query w.r.t. the reference neighborhood distance.
|
Modifier and Type | Method and Description |
---|---|
KNNQuery<O,D> |
LOF.LOFResult.getKNNReach() |
KNNQuery<O,D> |
LOF.LOFResult.getKNNRefer() |
Modifier and Type | Method and Description |
---|---|
private Pair<Pair<KNNQuery<O,D>,KNNQuery<O,D>>,Pair<RKNNQuery<O,D>,RKNNQuery<O,D>>> |
OnlineLOF.getKNNAndRkNNQueries(Relation<O> relation,
StepProgress stepprog)
Get the kNN and rkNN queries for the algorithm.
|
private Pair<Pair<KNNQuery<O,D>,KNNQuery<O,D>>,Pair<RKNNQuery<O,D>,RKNNQuery<O,D>>> |
OnlineLOF.getKNNAndRkNNQueries(Relation<O> relation,
StepProgress stepprog)
Get the kNN and rkNN queries for the algorithm.
|
protected Pair<KNNQuery<O,D>,KNNQuery<O,D>> |
LoOP.getKNNQueries(Database database,
Relation<O> relation,
StepProgress stepprog)
Get the kNN queries for the algorithm.
|
protected Pair<KNNQuery<O,D>,KNNQuery<O,D>> |
LoOP.getKNNQueries(Database database,
Relation<O> relation,
StepProgress stepprog)
Get the kNN queries for the algorithm.
|
private Pair<KNNQuery<O,D>,KNNQuery<O,D>> |
LOF.getKNNQueries(Relation<O> relation,
StepProgress stepprog)
Get the kNN queries for the algorithm.
|
private Pair<KNNQuery<O,D>,KNNQuery<O,D>> |
LOF.getKNNQueries(Relation<O> relation,
StepProgress stepprog)
Get the kNN queries for the algorithm.
|
Modifier and Type | Method and Description |
---|---|
protected Pair<WritableDataStore<Double>,DoubleMinMax> |
LOF.computeLOFs(DBIDs ids,
DataStore<Double> lrds,
KNNQuery<O,D> knnRefer)
Computes the Local outlier factor (LOF) of the specified objects.
|
protected WritableDataStore<Double> |
LOF.computeLRDs(DBIDs ids,
KNNQuery<O,D> knnReach)
Computes the local reachability density (LRD) of the specified objects.
|
protected LOF.LOFResult<O,D> |
LOF.doRunInTime(KNNQuery<O,D> kNNRefer,
KNNQuery<O,D> kNNReach,
StepProgress stepprog)
Performs the Generalized LOF_SCORE algorithm on the given database and
returns a
LOF.LOFResult encapsulating information that may be
needed by an OnlineLOF algorithm. |
protected LOF.LOFResult<O,D> |
LOF.doRunInTime(KNNQuery<O,D> kNNRefer,
KNNQuery<O,D> kNNReach,
StepProgress stepprog)
Performs the Generalized LOF_SCORE algorithm on the given database and
returns a
LOF.LOFResult encapsulating information that may be
needed by an OnlineLOF algorithm. |
Constructor and Description |
---|
LOF.LOFResult(OutlierResult result,
KNNQuery<O,D> kNNRefer,
KNNQuery<O,D> kNNReach,
WritableDataStore<Double> lrds,
WritableDataStore<Double> lofs)
Encapsulates information generated during a run of the
LOF
algorithm. |
LOF.LOFResult(OutlierResult result,
KNNQuery<O,D> kNNRefer,
KNNQuery<O,D> kNNReach,
WritableDataStore<Double> lrds,
WritableDataStore<Double> lofs)
Encapsulates information generated during a run of the
LOF
algorithm. |
Modifier and Type | Field and Description |
---|---|
private KNNQuery<O,D> |
KNNExplorer.ExplorerWindow.knnQuery
Holds the associated kNN query
|
Modifier and Type | Method and Description |
---|---|
static <O,D extends Distance<D>> |
QueryUtil.getKNNQuery(Database database,
DistanceFunction<? super O,D> distanceFunction,
Object... hints)
Get a KNN query object for the given distance function.
|
<O,D extends Distance<D>> |
AbstractDatabase.getKNNQuery(DistanceQuery<O,D> distanceQuery,
Object... hints) |
<O,D extends Distance<D>> |
Database.getKNNQuery(DistanceQuery<O,D> distanceQuery,
Object... hints)
Get a KNN query object for the given distance query.
|
static <O,D extends Distance<D>> |
QueryUtil.getKNNQuery(Relation<O> relation,
DistanceFunction<? super O,D> distanceFunction,
Object... hints)
Get a KNN query object for the given distance function.
|
static <O,D extends Distance<D>> |
QueryUtil.getLinearScanKNNQuery(DistanceQuery<O,D> distanceQuery)
Get a linear scan query for the given distance query.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractDistanceKNNQuery<O,D extends Distance<D>>
Instance for the query on a particular database.
|
class |
LinearScanKNNQuery<O,D extends Distance<D>>
Instance of this query for a particular database.
|
class |
LinearScanPrimitiveDistanceKNNQuery<O,D extends Distance<D>>
Instance of this query for a particular database.
|
class |
LinearScanRawDoubleDistanceKNNQuery<O>
Optimized linear scan query for
PrimitiveDoubleDistanceFunction s. |
class |
PreprocessorKNNQuery<O,D extends Distance<D>>
Instance for a particular database, invoking the preprocessor.
|
Modifier and Type | Field and Description |
---|---|
protected KNNQuery<O,D> |
LinearScanRKNNQuery.knnQuery
KNN query we use.
|
Constructor and Description |
---|
LinearScanRKNNQuery(DistanceQuery<O,D> distanceQuery,
KNNQuery<O,D> knnQuery,
Integer maxk)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
private KNNQuery<T,D> |
MinKDistance.Instance.knnQuery
KNN query instance
|
Modifier and Type | Method and Description |
---|---|
<D extends Distance<D>> |
KNNIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery,
Object... hints)
Get a KNN query object for the given distance query and k.
|
Modifier and Type | Field and Description |
---|---|
protected KNNQuery<O,D> |
MaterializeKNNPreprocessor.knnQuery
KNNQuery instance to use.
|
Modifier and Type | Method and Description |
---|---|
<S extends Distance<S>> |
AbstractMaterializeKNNPreprocessor.getKNNQuery(DistanceQuery<O,S> distanceQuery,
Object... hints) |
Modifier and Type | Field and Description |
---|---|
private KNNQuery<NV,DoubleDistance> |
KNNQueryFilteredPCAIndex.knnQuery
The kNN query instance we use
|
Constructor and Description |
---|
KNNQueryFilteredPCAIndex(Relation<NV> database,
PCAFilteredRunner<NV> pca,
KNNQuery<NV,DoubleDistance> knnQuery,
int k)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
<S extends Distance<S>> |
MkAppTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery,
Object... hints) |
Modifier and Type | Method and Description |
---|---|
<S extends Distance<S>> |
MkCoPTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery,
Object... hints) |
Modifier and Type | Method and Description |
---|---|
<S extends Distance<S>> |
MkMaxTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery,
Object... hints) |
Modifier and Type | Field and Description |
---|---|
private KNNQuery<O,D> |
MkTabTreeIndex.knnQuery
The knn query we use internally.
|
Modifier and Type | Method and Description |
---|---|
<S extends Distance<S>> |
MkTabTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery,
Object... hints) |
Modifier and Type | Method and Description |
---|---|
<S extends Distance<S>> |
MTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery,
Object... hints) |
Modifier and Type | Class and Description |
---|---|
class |
MetricalIndexKNNQuery<O,D extends Distance<D>>
Instance of a KNN query for a particular spatial index.
|
Modifier and Type | Method and Description |
---|---|
<D extends Distance<D>> |
DeLiCluTreeIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery,
Object... hints) |
Modifier and Type | Class and Description |
---|---|
class |
DoubleDistanceRStarTreeKNNQuery<O extends SpatialComparable>
Instance of a KNN query for a particular spatial index.
|
class |
GenericRStarTreeKNNQuery<O extends SpatialComparable,D extends Distance<D>>
Instance of a KNN query for a particular spatial index.
|
Modifier and Type | Method and Description |
---|---|
static <O extends SpatialComparable,D extends Distance<D>> |
RStarTreeUtil.getKNNQuery(AbstractRStarTree<?,?> tree,
SpatialDistanceQuery<O,D> distanceQuery,
Object... hints)
Get an RTree knn query, using an optimized double implementation when
possible.
|
Modifier and Type | Method and Description |
---|---|
<D extends Distance<D>> |
RStarTreeIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery,
Object... hints) |